Method and apparatus for verifying discriminating of tachycardia events in a medical device having dual sensing vectors

ABSTRACT

A method and medical device for detecting a cardiac event that includes sensing cardiac signals from a plurality of electrodes, sensing a plurality of beats in response to the sensed cardiac signals, identifying each beat of the plurality of beats as one of a normal beat and a not normal beat, determining at least one of whether a number of beats identified as a normal beat is greater than a normal beat threshold, whether an RR interval associated with the beats identified as being a normal beat is less than a threshold interval, and whether RR intervals associated with the beats identified as being normal beats are within an RR interval range, and identifying the cardiac event as being one of shockable and not shockable in response to the determining.

RELATED APPLICATION

The present application is a continuation of U.S. patent applicationSer. No. 14/339,156, filed Jul. 23, 2014 (now granted), entitled “METHODAND APPARATUS FOR VERIFYING DISCRIMINATING OF TACHYCARDIA EVENTS IN AMEDICAL DEVICE HAVING DUAL SENSING VECTORS,” which claims priority andother benefits from U.S. Provisional Patent Application Ser. No.62/019,658, filed Jul. 1, 2014, both of which are incorporated herein byreference in their entirety.

TECHNICAL FIELD

The disclosure relates generally to implantable medical devices and, inparticular, to an apparatus and method for discriminating arrhythmiasand delivering a therapy in a medical device.

BACKGROUND

Implantable medical devices are available for treating cardiactachyarrhythmias by delivering anti-tachycardia pacing therapies andelectrical shock therapies for cardioverting or defibrillating theheart. Such a device, commonly known as an implantable cardioverterdefibrillator or “ICD”, senses electrical activity from the heart,determines a patient's heart rate, and classifies the rate according toa number of heart rate zones in order to detect episodes of ventriculartachycardia or fibrillation. Typically a number of rate zones aredefined according to programmable detection interval ranges fordetecting slow ventricular tachycardia, fast ventricular tachycardia andventricular fibrillation. Intervals between sensed R-waves,corresponding to the depolarization of the ventricles, are measured.Sensed R-R intervals falling into defined detection interval ranges arecounted to provide a count of ventricular tachycardia (VT) orventricular fibrillation (VF) intervals, for example. A programmablenumber of intervals to detect (NID) defines the number of tachycardiaintervals occurring consecutively or out of a given number of precedingevent intervals that are required to detect VT or VF.

Tachyarrhythmia detection may begin with detecting a fast ventricularrate, referred to as rate- or interval-based detection. Once VT or VF isdetected based on rate, the morphology of the sensed depolarizationsignals, e.g. wave shape, amplitude or other features, may be used indiscriminating heart rhythms to improve the sensitivity and specificityof tachyarrhythmia detection methods.. A primary goal of a tachycardiadetection algorithm is to rapidly respond to a potentially malignantrhythm with a therapy that will terminate the arrhythmia with highcertainty. Another goal, however, is to avoid excessive use of ICDbattery charge, which shortens the life of the ICD, e.g. due todelivering unnecessary therapies or therapies at a higher voltage thanneeded to terminate a detected tachyarrhythmia. Minimizing the patient'sexposure to painful shock therapies is also an important consideration.Accordingly, a need remains for ICDs that perform tachycardiadiscrimination with high specificity and control therapy delivery tosuccessfully terminate a detected VT requiring therapy while conservingbattery charge and limiting patient exposure to delivered shock therapyby withholding therapy delivery whenever possible in situations wherethe therapy may not be required.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a conceptual diagram of a patient implanted with an exampleextravascular cardiac defibrillation system.

FIG. 2 is an exemplary schematic diagram of electronic circuitry withina hermetically sealed housing of a subcutaneous device according to anembodiment of the present invention.

FIG. 3 is a state diagram of detection of arrhythmias in a medicaldevice according to an embodiment of the present invention.

FIG. 4 is a flowchart of a method for detecting arrhythmias in asubcutaneous device according to an embodiment of the presentdisclosure.

FIG. 5 is a flowchart of a method of determining noise according to anembodiment of the present disclosure.

FIG. 6A is a graphical representation of a determination of whether asignal is corrupted by muscle noise according to an embodiment of thepresent invention.

FIG. 6B is a flowchart of a method of determining whether a signal iscorrupted by muscle noise according to an embodiment of the presentinvention.

FIG. 6C is a flowchart of a method of determining whether a signal iscorrupted by muscle noise according to an embodiment of the presentinvention.

FIG. 7 is a graphical representation of a VF shock zone according to anembodiment of the present invention.

FIGS. 8A and 8B are graphical representations of the determination ofwhether an event is within a shock zone according to an embodiment ofthe present invention.

FIG. 9 is a flowchart of a method for discriminating cardiac eventsaccording to an embodiment of the disclosure.

FIG. 10 is a flowchart of a method for performing periodic normal beatsanalysis during detection of arrhythmias in a medical device, accordingto an embodiment of the present disclosure.

FIG. 11 is a flowchart of a method for aligning an ECG signal of anunknown beat with a known morphology template for beat-based analysisduring detection of arrhythmias in a medical device, according to anembodiment of the present disclosure.

FIG. 12 is a flowchart of a method for computing a morphology metric todetermine the similarity between a known template aligned with anunknown cardiac cycle signal according to one embodiment.

FIG. 13 is an exemplary plot of alignment of an unknown beat and atemplate for computing a normalized waveform area difference duringbeat-based analysis, according to one embodiment.

FIG. 14 is an exemplary plot illustrating a technique for determining anR-wave width and computing a normalized waveform area difference duringbeat-based analysis, according to another embodiment.

FIG. 15 is a flowchart of an exemplary method for determining whetherperiodic normal beats are detected within a predetermined sensing vectorduring the periodic normal beats analysis of FIG. 10.

FIG. 16 is a schematic diagram of an exemplary cardiac signal sensedwithin a sensing detection window during detection of a cardiac event.

FIG. 17 is a flowchart of an exemplary method for determining whetherperiodic normal beats are detected within a predetermined sensing vectorduring the periodic normal beats analysis of FIG. 10.

DETAILED DESCRIPTION

FIG. 1 is a conceptual diagram of a patient 12 implanted with an exampleextravascular cardiac defibrillation system 10. In the exampleillustrated in FIG. 1, extravascular cardiac defibrillation system 10 isan implanted subcutaneous ICD system. However, the techniques of thisdisclosure may also be utilized with other extravascular implantedcardiac defibrillation systems, such as a cardiac defibrillation systemhaving a lead implanted at least partially in a substernal orsubmuscular location. Additionally, the techniques of this disclosuremay also be utilized with other implantable systems, such as implantablepacing systems, implantable neurostimulation systems, drug deliverysystems or other systems in which leads, catheters or other componentsare implanted at extravascular locations within patient 12. Thisdisclosure, however, is described in the context of an implantableextravascular cardiac defibrillation system for purposes ofillustration.

Extravascular cardiac defibrillation system 10 includes an implantablecardioverter defibrillator (ICD) 14 connected to at least oneimplantable cardiac defibrillation lead 16. ICD 14 of FIG. 1 isimplanted subcutaneously on the left side of patient 12. Defibrillationlead 16, which is connected to ICD 14, extends medially from ICD 14toward sternum 28 and xiphoid process 24 of patient 12. At a locationnear xiphoid process 24, defibrillation lead 16 bends or turns andextends subcutaneously superior, substantially parallel to sternum 28.In the example illustrated in FIG. 1, defibrillation lead 16 isimplanted such that lead 16 is offset laterally to the left side of thebody of sternum 28 (i.e., towards the left side of patient 12).

Defibrillation lead 16 is placed along sternum 28 such that a therapyvector between defibrillation electrode 18 and a second electrode (suchas a housing or can 25 of ICD 14 or an electrode placed on a secondlead) is substantially across the ventricle of heart 26. The therapyvector may, in one example, be viewed as a line that extends from apoint on the defibrillation electrode 18 to a point on the housing orcan 25 of ICD 14. In another example, defibrillation lead 16 may beplaced along sternum 28 such that a therapy vector betweendefibrillation electrode 18 and the housing or can 25 of ICD 14 (orother electrode) is substantially across an atrium of heart 26. In thiscase, extravascular ICD system 10 may be used to provide atrialtherapies, such as therapies to treat atrial fibrillation.

The embodiment illustrated in FIG. 1 is an example configuration of anextravascular ICD system 10 and should not be considered limiting of thetechniques described herein. For example, although illustrated as beingoffset laterally from the midline of sternum 28 in the example of FIG.1, defibrillation lead 16 may be implanted such that lead 16 is offsetto the right of sternum 28 or more centrally located over sternum 28.Additionally, defibrillation lead 16 may be implanted such that it isnot substantially parallel to sternum 28, but instead offset fromsternum 28 at an angle (e.g., angled lateral from sternum 28 at eitherthe proximal or distal end). As another example, the distal end ofdefibrillation lead 16 may be positioned near the second or third rib ofpatient 12. However, the distal end of defibrillation lead 16 may bepositioned further superior or inferior depending on the location of ICD14, location of electrodes 18, 20, and 22, or other factors.

Although ICD 14 is illustrated as being implanted near a midaxillaryline of patient 12, ICD 14 may also be implanted at other subcutaneouslocations on patient 12, such as further posterior on the torso towardthe posterior axillary line, further anterior on the torso toward theanterior axillary line, in a pectoral region, or at other locations ofpatient 12. In instances in which ICD 14 is implanted pectorally, lead16 would follow a different path, e.g., across the upper chest area andinferior along sternum 28. When the ICD 14 is implanted in the pectoralregion, the extravascular ICD system may include a second lead includinga defibrillation electrode that extends along the left side of thepatient such that the defibrillation electrode of the second lead islocated along the left side of the patient to function as an anode orcathode of the therapy vector of such an ICD system.

ICD 14 includes a housing or can 25 that forms a hermetic seal thatprotects components within ICD 14. The housing 25 of ICD 14 may beformed of a conductive material, such as titanium or other biocompatibleconductive material or a combination of conductive and non-conductivematerials. In some instances, the housing 25 of ICD 14 functions as anelectrode (referred to as a housing electrode or can electrode) that isused in combination with one of electrodes 18, 20, or 22 to deliver atherapy to heart 26 or to sense electrical activity of heart 26. ICD 14may also include a connector assembly (sometimes referred to as aconnector block or header) that includes electrical feedthroughs throughwhich electrical connections are made between conductors withindefibrillation lead 16 and electronic components included within thehousing. Housing may enclose one or more components, includingprocessors, memories, transmitters, receivers, sensors, sensingcircuitry, therapy circuitry and other appropriate components (oftenreferred to herein as modules).

Defibrillation lead 16 includes a lead body having a proximal end thatincludes a connector configured to connect to ICD 14 and a distal endthat includes one or more electrodes 18, 20, and 22. The lead body ofdefibrillation lead 16 may be formed from a non-conductive material,including silicone, polyurethane, fluoropolymers, mixtures thereof, andother appropriate materials, and shaped to form one or more lumenswithin which the one or more conductors extend. However, the techniquesare not limited to such constructions. Although defibrillation lead 16is illustrated as including three electrodes 18, 20 and 22,defibrillation lead 16 may include more or fewer electrodes.

Defibrillation lead 16 includes one or more elongated electricalconductors (not illustrated) that extend within the lead body from theconnector on the proximal end of defibrillation lead 16 to electrodes18, 20 and 22. In other words, each of the one or more elongatedelectrical conductors contained within the lead body of defibrillationlead 16 may engage with respective ones of electrodes 18, 20 and 22.When the connector at the proximal end of defibrillation lead 16 isconnected to ICD 14, the respective conductors may electrically coupleto circuitry, such as a therapy module or a sensing module, of ICD 14via connections in connector assembly, including associatedfeedthroughs. The electrical conductors transmit therapy from a therapymodule within ICD 14 to one or more of electrodes 18, 20 and 22 andtransmit sensed electrical signals from one or more of electrodes 18, 20and 22 to the sensing module within ICD 14.

ICD 14 may sense electrical activity of heart 26 via one or more sensingvectors that include combinations of electrodes 20 and 22 and thehousing or can 25 of ICD 14. For example, ICD 14 may obtain electricalsignals sensed using a sensing vector between electrodes 20 and 22,obtain electrical signals sensed using a sensing vector betweenelectrode 20 and the conductive housing or can 25 of ICD 14, obtainelectrical signals sensed using a sensing vector between electrode 22and the conductive housing or can 25 of ICD 14, or a combinationthereof. In some instances, ICD 14 may sense cardiac electrical signalsusing a sensing vector that includes defibrillation electrode 18, suchas a sensing vector between defibrillation electrode 18 and one ofelectrodes 20 or 22, or a sensing vector between defibrillationelectrode 18 and the housing or can 25 of ICD 14.

ICD may analyze the sensed electrical signals to detect tachycardia,such as ventricular tachycardia or ventricular fibrillation, and inresponse to detecting tachycardia may generate and deliver an electricaltherapy to heart 26. For example, ICD 14 may deliver one or moredefibrillation shocks via a therapy vector that includes defibrillationelectrode 18 of defibrillation lead 16 and the housing or can 25.Defibrillation electrode 18 may, for example, be an elongated coilelectrode or other type of electrode. In some instances, ICD 14 maydeliver one or more pacing therapies prior to or after delivery of thedefibrillation shock, such as anti-tachycardia pacing (ATP) or postshock pacing. In these instances,

ICD 14 may generate and deliver pacing pulses via therapy vectors thatinclude one or both of electrodes 20 and 22 and/or the housing or can25. Electrodes 20 and 22 may comprise ring electrodes, hemisphericalelectrodes, coil electrodes, helix electrodes, segmented electrodes,directional electrodes, or other types of electrodes, or combinationthereof. Electrodes 20 and 22 may be the same type of electrodes ordifferent types of electrodes, although in the example of FIG. 1 bothelectrodes 20 and 22 are illustrated as ring electrodes.

Defibrillation lead 16 may also include an attachment feature 29 at ortoward the distal end of lead 16. The attachment feature 29 may be aloop, link, or other attachment feature. For example, attachment feature29 may be a loop formed by a suture. As another example, attachmentfeature 29 may be a loop, link, ring of metal, coated metal or apolymer. The attachment feature 29 may be formed into any of a number ofshapes with uniform or varying thickness and varying dimensions.Attachment feature 29 may be integral to the lead or may be added by theuser prior to implantation. Attachment feature 29 may be useful to aidin implantation of lead 16 and/or for securing lead 16 to a desiredimplant location. In some instances, defibrillation lead 16 may includea fixation mechanism in addition to or instead of the attachmentfeature. Although defibrillation lead 16 is illustrated with anattachment feature 29, in other examples lead 16 may not include anattachment feature 29.

Lead 16 may also include a connector at the proximal end of lead 16,such as a DF4 connector, bifurcated connector (e.g., DF-1/IS-1connector), or other type of connector. The connector at the proximalend of lead 16 may include a terminal pin that couples to a port withinthe connector assembly of ICD 14. In some instances, lead 16 may includean attachment feature at the proximal end of lead 16 that may be coupledto an implant tool to aid in implantation of lead 16. The attachmentfeature at the proximal end of the lead may separate from the connectorand may be either integral to the lead or added by the user prior toimplantation.

Defibrillation lead 16 may also include a suture sleeve or otherfixation mechanism (not shown) located proximal to electrode 22 that isconfigured to fixate lead 16 near the xiphoid process or lower sternumlocation. The fixation mechanism (e.g., suture sleeve or othermechanism) may be integral to the lead or may be added by the user priorto implantation.

The example illustrated in FIG. 1 is exemplary in nature and should notbe considered limiting of the techniques described in this disclosure.For instance, extravascular cardiac defibrillation system 10 may includemore than one lead. In one example, extravascular cardiac defibrillationsystem 10 may include a pacing lead in addition to defibrillation lead16.

In the example illustrated in FIG. 1, defibrillation lead 16 isimplanted subcutaneously, e.g., between the skin and the ribs orsternum. In other instances, defibrillation lead 16 (and/or the optionalpacing lead) may be implanted at other extravascular locations. In oneexample, defibrillation lead 16 may be implanted at least partially in asubsternal location. In such a configuration, at least a portion ofdefibrillation lead 16 may be placed under or below the sternum in themediastinum and, more particularly, in the anterior mediastinum. Theanterior mediastinum is bounded laterally by pleurae, posteriorly bypericardium, and anteriorly by sternum 28. Defibrillation lead 16 may beat least partially implanted in other extra-pericardial locations, i.e.,locations in the region around, but not in direct contact with, theouter surface of heart 26. These other extra-pericardial locations mayinclude in the mediastinum but offset from sternum 28, in the superiormediastinum, in the middle mediastinum, in the posterior mediastinum, inthe sub-xiphoid or inferior xiphoid area, near the apex of the heart, orother location not in direct contact with heart 26 and not subcutaneous.In still further instances, the lead may be implanted at a pericardialor epicardial location outside of the heart 26.

FIG. 2 is an exemplary schematic diagram of electronic circuitry withina hermetically sealed housing of a subcutaneous device according to anembodiment of the present invention. As illustrated in FIG. 2,subcutaneous device 14 includes a low voltage battery 153 coupled to apower supply (not shown) that supplies power to the circuitry of thesubcutaneous device 14 and the pacing output capacitors to supply pacingenergy in a manner well known in the art. The low voltage battery 153may be formed of one or two conventional LiCF_(x), LiMnO₂ or LiI₂ cells,for example. The subcutaneous device 14 also includes a high voltagebattery 112 that may be formed of one or two conventional LiSVO orLiMnO₂ cells. Although two both low voltage battery and a high voltagebattery are shown in FIG. 2, according to an embodiment of the presentinvention, the device 14 could utilize a single battery for both highand low voltage uses.

Further referring to FIG. 2, subcutaneous device 14 functions arecontrolled by means of software, firmware and hardware thatcooperatively monitor the ECG signal, determine when acardioversion-defibrillation shock or pacing is necessary, and deliverprescribed cardioversion-defibrillation and pacing therapies. Thesubcutaneous device 14 may incorporate circuitry set forth in commonlyassigned U.S. Pat. Nos. 5,163,427 “Apparatus for Delivering Single andMultiple Cardioversion and Defibrillation Pulses” to Keimel and U.S.Pat. No. 5,188,105 “Apparatus and Method for Treating a Tachyarrhythmia”to Keimel for selectively delivering single phase, simultaneous biphasicand sequential biphasic cardioversion-defibrillation shocks typicallyemploying ICD IPG housing electrodes 28 coupled to the COMMON output 123of high voltage output circuit 140 and cardioversion-defibrillationelectrode 24 disposed posterially and subcutaneously and coupled to theHVI output 113 of the high voltage output circuit 140.

The cardioversion-defibrillation shock energy and capacitor chargevoltages can be intermediate to those supplied by ICDs having at leastone cardioversion-defibrillation electrode in contact with the heart andmost AEDs having cardioversion-defibrillation electrodes in contact withthe skin. The typical maximum voltage necessary for ICDs using mostbiphasic waveforms is approximately 750 Volts with an associated maximumenergy of approximately 40 Joules. The typical maximum voltage necessaryfor AEDs is approximately 2000-5000 Volts with an associated maximumenergy of approximately 200-360 Joules depending upon the model andwaveform used. The subcutaneous device 14 of the present invention usesmaximum voltages in the range of about 300 to approximately 1000 Voltsand is associated with energies of approximately 25 to 150 joules ormore. The total high voltage capacitance could range from about 50 toabout 300 microfarads. Such cardioversion-defibrillation shocks are onlydelivered when a malignant tachyarrhythmia, e.g., ventricularfibrillation is detected through processing of the far field cardiac ECGemploying the detection algorithms as described herein below.

In FIG. 2, sense amp 190 in conjunction with pacer/device timing circuit178 processes the far field ECG sense signal that is developed across aparticular ECG sense vector defined by a selected pair of thesubcutaneous electrodes 18, 20, 22 and the can or housing 25 of thedevice 14, or, optionally, a virtual signal (i.e., a mathematicalcombination of two vectors) if selected. The selection of the sensingelectrode pair is made through the switch matrix/MUX 191 in a manner toprovide the most reliable sensing of the ECG signal of interest, whichwould be the R wave for patients who are believed to be at risk ofventricular fibrillation leading to sudden death. The far field ECGsignals are passed through the switch matrix/MUX 191 to the input of thesense amplifier 190 that, in conjunction with pacer/device timingcircuit 178, evaluates the sensed EGM. Bradycardia, or asystole, istypically determined by an escape interval timer within the pacer timingcircuit 178 and/or the control circuit 144. Pace Trigger signals areapplied to the pacing pulse generator 192 generating pacing stimulationwhen the interval between successive R-waves exceeds the escapeinterval. Bradycardia pacing is often temporarily provided to maintaincardiac output after delivery of a cardioversion-defibrillation shockthat may cause the heart to slowly beat as it recovers back to normalfunction. Sensing subcutaneous far field signals in the presence ofnoise may be aided by the use of appropriate denial and extensibleaccommodation periods as described in U.S. Pat. No. 6,236,882 “NoiseRejection for Monitoring ECGs” to Lee, et al and incorporated herein byreference in its' entirety.

Detection of a malignant tachyarrhythmia is determined in the Controlcircuit 144 as a function of the intervals between R-wave sense eventsignals that are output from the pacer/device timing 178 and senseamplifier circuit 190 to the timing and control circuit 144. It shouldbe noted that the present invention utilizes not only interval basedsignal analysis method but also supplemental sensors and morphologyprocessing method and apparatus as described herein below.

Supplemental sensors such as tissue color, tissue oxygenation,respiration, patient activity and the like may be used to contribute tothe decision to apply or withhold a defibrillation therapy as describedgenerally in U.S. Pat. No. 5,464,434 “Medical Interventional DeviceResponsive to Sudden Hemodynamic Change” to Alt and incorporated hereinby reference in its entirety. Sensor processing block 194 providessensor data to microprocessor 142 via data bus 146. Specifically,patient activity and/or posture may be determined by the apparatus andmethod as described in U.S. Pat. No. 5,593,431 “Medical ServiceEmploying Multiple DC Accelerometers for Patient Activity and PostureSensing and Method” to Sheldon and incorporated herein by reference inits entirety. Patient respiration may be determined by the apparatus andmethod as described in U.S. Pat. No. 4,567,892 “Implantable CardiacPacemaker” to Plicchi, et al and incorporated herein by reference in itsentirety. Patient tissue oxygenation or tissue color may be determinedby the sensor apparatus and method as described in U.S. Pat. No.5,176,137 to Erickson, et al and incorporated herein by reference in itsentirety. The oxygen sensor of the '137 patent may be located in thesubcutaneous device pocket or, alternatively, located on the lead 18 toenable the sensing of contacting or near-contacting tissue oxygenationor color.

Certain steps in the performance of the detection algorithm criteria arecooperatively performed in microcomputer 142, including microprocessor,RAM and ROM, associated circuitry, and stored detection criteria thatmay be programmed into RAM via a telemetry interface (not shown)conventional in the art. Data and commands are exchanged betweenmicrocomputer 142 and timing and control circuit 144, pacertiming/amplifier circuit 178, and high voltage output circuit 140 via abi-directional data/control bus 146. The pacer timing/amplifier circuit178 and the control circuit 144 are clocked at a slow clock rate. Themicrocomputer 142 is normally asleep, but is awakened and operated by afast clock by interrupts developed by each R-wave sense event, onreceipt of a downlink telemetry programming instruction or upon deliveryof cardiac pacing pulses to perform any necessary mathematicalcalculations, to perform tachycardia and fibrillation detectionprocedures, and to update the time intervals monitored and controlled bythe timers in pacer/device timing circuitry 178.

When a malignant tachycardia is detected, high voltage capacitors 156,158, 160, and 162 are charged to a pre-programmed voltage level by ahigh-voltage charging circuit 164. It is generally consideredinefficient to maintain a constant charge on the high voltage outputcapacitors 156, 158, 160, 162. Instead, charging is initiated whencontrol circuit 144 issues a high voltage charge command HVCHG deliveredon line 145 to high voltage charge circuit 164 and charging iscontrolled by means of bi-directional control/data bus 166 and afeedback signal VCAP from the HV output circuit 140. High voltage outputcapacitors 156, 158, 160 and 162 may be of film, aluminum electrolyticor wet tantalum construction.

The negative terminal of high voltage battery 112 is directly coupled tosystem ground. Switch circuit 114 is normally open so that the positiveterminal of high voltage battery 112 is disconnected from the positivepower input of the high voltage charge circuit 164. The high voltagecharge command HVCHG is also conducted via conductor 149 to the controlinput of switch circuit 114, and switch circuit 114 closes in responseto connect positive high voltage battery voltage EXT B+ to the positivepower input of high voltage charge circuit 164. Switch circuit 114 maybe, for example, a field effect transistor (FET) with itssource-to-drain path interrupting the EXT B+ conductor 118 and its gatereceiving the HVCHG signal on conductor 145. High voltage charge circuit164 is thereby rendered ready to begin charging the high voltage outputcapacitors 156, 158, 160, and 162 with charging current from highvoltage battery 112.

High voltage output capacitors 156, 158, 160, and 162 may be charged tovery high voltages, e.g., 300-1000V, to be discharged through the bodyand heart between the electrode pair of subcutaneouscardioversion-defibrillation electrodes 113 and 123. The details of thevoltage charging circuitry are also not deemed to be critical withregard to practicing the present invention; one high voltage chargingcircuit believed to be suitable for the purposes of the presentinvention is disclosed. High voltage capacitors 156, 158, 160 and 162may be charged, for example, by high voltage charge circuit 164 and ahigh frequency, high-voltage transformer 168 as described in detail incommonly assigned U.S. Pat. No. 4,548,209 “Energy Converter forImplantable Cardioverter” to Wielders, et al. Proper charging polaritiesare maintained by diodes 170, 172, 174 and 176 interconnecting theoutput windings of high-voltage transformer 168 and the capacitors 156,158, 160, and 162. As noted above, the state of capacitor charge ismonitored by circuitry within the high voltage output circuit 140 thatprovides a VCAP, feedback signal indicative of the voltage to the timingand control circuit 144. Timing and control circuit 144 terminates thehigh voltage charge command HVCHG when the VCAP signal matches theprogrammed capacitor output voltage, i.e., thecardioversion-defibrillation peak shock voltage.

Control circuit 144 then develops first and second control signalsNPULSE 1 and NPULSE 2, respectively, that are applied to the highvoltage output circuit 140 for triggering the delivery of cardiovertingor defibrillating shocks. In particular, the NPULSE 1 signal triggersdischarge of the first capacitor bank, comprising capacitors 156 and158. The NPULSE 2 signal triggers discharge of the first capacitor bankand a second capacitor bank, comprising capacitors 160 and 162. It ispossible to select between a plurality of output pulse regimes simply bymodifying the number and time order of assertion of the NPULSE 1 andNPULSE 2 signals. The NPULSE 1 signals and NPULSE 2 signals may beprovided sequentially, simultaneously or individually. In this way,control circuitry 144 serves to control operation of the high voltageoutput stage 140, which delivers high energycardioversion-defibrillation shocks between the pair of thecardioversion-defibrillation electrodes 18 and 25 coupled to the HV-1and COMMON output as shown in FIG. 2.

Thus, subcutaneous device 14 monitors the patient's cardiac status andinitiates the delivery of a cardioversion-defibrillation shock throughthe cardioversion-defibrillation electrodes 18 and 25 in response todetection of a tachyarrhythmia requiring cardioversion-defibrillation.The high HVCHG signal causes the high voltage battery 112 to beconnected through the switch circuit 114 with the high voltage chargecircuit 164 and the charging of output capacitors 156, 158, 160, and 162to commence. Charging continues until the programmed charge voltage isreflected by the VCAP signal, at which point control and timing circuit144 sets the HVCHG signal low terminating charging and opening switchcircuit 114. The subcutaneous device 14 can be programmed to attempt todeliver cardioversion shocks to the heart in the manners described abovein timed synchrony with a detected R-wave or can be programmed orfabricated to deliver defibrillation shocks to the heart in the mannersdescribed above without attempting to synchronize the delivery to adetected R-wave. Episode data related to the detection of thetachyarrhythmia and delivery of the cardioversion-defibrillation shockcan be stored in RAM for uplink telemetry transmission to an externalprogrammer as is well known in the art to facilitate in diagnosis of thepatient's cardiac state. A patient receiving the device 14 on aprophylactic basis would be instructed to report each such episode tothe attending physician for further evaluation of the patient'scondition and assessment for the need for implantation of a moresophisticated ICD.

Subcutaneous device 14 desirably includes telemetry circuit (not shownin FIG. 2), so that it is capable of being programmed by means ofexternal programmer 20 via a 2-way telemetry link (not shown). Uplinktelemetry allows device status and diagnostic/event data to be sent toexternal programmer 20 for review by the patient's physician. Downlinktelemetry allows the external programmer via physician control to allowthe programming of device function and the optimization of the detectionand therapy for a specific patient. Programmers and telemetry systemssuitable for use in the practice of the present invention have been wellknown for many years. Known programmers typically communicate with animplanted device via a bi-directional radio-frequency telemetry link, sothat the programmer can transmit control commands and operationalparameter values to be received by the implanted device, so that theimplanted device can communicate diagnostic and operational data to theprogrammer. Programmers believed to be suitable for the purposes ofpracticing the present invention include the Models 9790 and CareLink®programmers, commercially available from Medtronic, Inc., Minneapolis,Minn.

Various telemetry systems for providing the necessary communicationschannels between an external programming unit and an implanted devicehave been developed and are well known in the art. Telemetry systemsbelieved to be suitable for the purposes of practicing the presentinvention are disclosed, for example, in the following U.S. Patents:U.S. Pat. No. 5, 127,404 to Wyborny et al. entitled “Telemetry Formatfor Implanted Medical Device”; U.S. Pat. No. 4,374,382 to Markowitzentitled “Marker Channel Telemetry System for a Medical Device”; andU.S. Pat. No. 4,556, 063 to Thompson et al. entitled “Telemetry Systemfor a Medical Device”. The Wyborny et al. '404, Markowitz '382, andThompson et al. '063 patents are commonly assigned to the assignee ofthe present invention, and are each hereby incorporated by referenceherein in their respective entireties.

According to an embodiment of the present invention, in order toautomatically select the preferred ECG vector set, it is necessary tohave an index of merit upon which to rate the quality of the signal.“Quality” is defined as the signal's ability to provide accurate heartrate estimation and accurate morphological waveform separation betweenthe patient's usual sinus rhythm and the patient's ventriculartachyarrhythmia.

Appropriate indices may include R-wave amplitude, R-wave peak amplitudeto waveform amplitude between R-waves (i.e., signal to noise ratio), lowslope content, relative high versus low frequency power, mean frequencyestimation, probability density function, or some combination of thesemetrics.

Automatic vector selection might be done at implantation or periodically(daily, weekly, monthly) or both. At implant, automatic vector selectionmay be initiated as part of an automatic device turn-on procedure thatperforms such activities as measure lead impedances and batteryvoltages. The device turn-on procedure may be initiated by theimplanting physician (e.g., by pressing a programmer button) or,alternatively, may be initiated automatically upon automatic detectionof device/lead implantation. The turn-on procedure may also use theautomatic vector selection criteria to determine if ECG vector qualityis adequate for the current patient and for the device and leadposition, prior to suturing the subcutaneous device 14 device in placeand closing the incision. Such an ECG quality indicator would allow theimplanting physician to maneuver the device to a new location ororientation to improve the quality of the ECG signals as required. Thepreferred ECG vector or vectors may also be selected at implant as partof the device turn-on procedure. The preferred vectors might be thosevectors with the indices that maximize rate estimation and detectionaccuracy. There may also be an a priori set of vectors that arepreferred by the physician, and as long as those vectors exceed someminimum threshold, or are only slightly worse than some other moredesirable vectors, the a priori preferred vectors are chosen. Certainvectors may be considered nearly identical such that they are not testedunless the a priori selected vector index falls below some predeterminedthreshold.

Depending upon metric power consumption and power requirements of thedevice, the ECG signal quality metric may be measured on the range ofvectors (or alternatively, a subset) as often as desired. Data may begathered, for example, on a minute, hourly, daily, weekly or monthlybasis. More frequent measurements (e.g., every minute) may be averagedover time and used to select vectors based upon susceptibility ofvectors to occasional noise, motion noise, or EMI, for example.

Alternatively, the subcutaneous device 14 may have an indicator/sensorof patient activity (piezo-resistive, accelerometer, impedance, or thelike) and delay automatic vector measurement during periods of moderateor high patient activity to periods of minimal to no activity. Onerepresentative scenario may include testing/evaluating ECG vectors oncedaily or weekly while the patient has been determined to be asleep(using an internal clock (e.g., 2:00 am) or, alternatively, infer sleepby determining the patient's position (via a 2- or 3-axis accelerometer)and a lack of activity).

If infrequent automatic, periodic measurements are made, it may also bedesirable to measure noise (e.g., muscle, motion, EMI, etc.) in thesignal and postpone the vector selection measurement when the noise hassubsided.

Subcutaneous device 14 may optionally have an indicator of the patient'sposture (via a 2- or 3-axis accelerometer). This sensor may be used toensure that the differences in ECG quality are not simply a result ofchanging posture/position. The sensor may be used to gather data in anumber of postures so that ECG quality may be averaged over thesepostures or, alternatively, selected for a preferred posture.

In the preferred embodiment, vector quality metric calculations wouldoccur a number of times over approximately 1 minute, once per day, foreach vector. These values would be averaged for each vector over thecourse of one week. Averaging may consist of a moving average orrecursive average depending on time weighting and memory considerations.In this example, the preferred vector(s) would be selected once perweek.

FIG. 3 is a state diagram of detection of arrhythmias in a medicaldevice according to an embodiment of the present invention. Asillustrated in FIG. 3, during normal operation, the device 14 is in anot concerned state 302, during which R-wave intervals are beingevaluated to identify periods of rapid rates and/or the presence ofasystole. Upon detection of short R-wave intervals simultaneously in twoseparate ECG sensing vectors, indicative of an event that, if confirmed,may require the delivery of therapy, the device 14 transitions from thenot concerned state 302 to a concerned state 304. In the concerned state304 the device 14 evaluates a predetermined window of ECG signals todetermine the likelihood that the signal is corrupted with noise and todiscriminate rhythms requiring shock therapy from those that do notrequire shock therapy, using a combination of R-wave intervals and ECGsignal morphology information.

If a rhythm requiring shock therapy continues to be detected while inthe concerned state 304, the device 14 transitions from the concernedstate 304 to an armed state 306. If a rhythm requiring shock therapy isno longer detected while the device is in the concerned state 304 andthe R-wave intervals are determined to no longer be short, the device 14returns to the not concerned state 302. However, if a rhythm requiringshock therapy is no longer detected while the device is in the concernedstate 304, but the R-wave intervals continue to be detected as beingshort, processing continues in the concerned state 304.

In the armed state 306, the device 14 charges the high voltage shockingcapacitors and continues to monitor R-wave intervals and ECG signalmorphology for spontaneous termination. If spontaneous termination ofthe rhythm requiring shock therapy occurs, the device 14 returns to thenot concerned state 302. If the rhythm requiring shock therapy is stilldetermined to be occurring once the charging of the capacitors iscompleted, the device 14 transitions from the armed state 306 to a shockstate 308. In the shock state 308, the device 14 delivers a shock andreturns to the armed state 306 to evaluate the success of the therapydelivered.

The transitioning between the not concerned state 302, the concernedstate 304, the armed state 306 and the shock state 308 may be performedas described in detail in U.S. Pat. No. 7,894,894 to Stadler et al.,incorporated herein by reference in it's entirety.

FIG. 4 is a flowchart of a method for detecting arrhythmias in asubcutaneous device according to an embodiment of the presentdisclosure. As illustrated in FIG. 4, device 14 continuously evaluatesthe two channels ECG1 and ECG2 associated with two predeterminedelectrode vectors to determine when sensed events occur. For example,the electrode vectors for the two channels ECG1 and ECG2 may include afirst vector (ECG1) selected between electrode 20 positioned on lead 16and the housing or can 25 of ICD 14, while the other electrode vector(ECG 2) is a vertical electrode vector between electrode 20 andelectrode 22 positioned along the lead 16. However, the two sensingchannels may in any combination of possible vectors, including thoseformed by the electrodes shown in FIG.2, or other additional electrodes(not shown) that may be included along the lead or positioned along thehousing of ICD 14.

According to an embodiment of the present application, for example, thedevice 14 determines whether to transition from the not concerned state302 to the concerned state 304 by determining a heart rate estimate inresponse to the sensing of R-waves, as described in U.S. Pat. No.7,894,894 to Stadler et al., incorporated herein by reference in it'sentirety.

Upon transition from the not concerned state to the concerned state,Block 305, a most recent window of ECG data from both channels ECG1 andECG2 are utilized, such as three seconds, for example, so thatprocessing is triggered in the concerned state 304 by a three-secondtimeout, rather than by the sensing of an R-wave, which is utilized whenin the not concerned state 302. It is understood that while theprocessing is described as being triggered over a three second period,other times periods for the processing time utilized when in theconcerned state 304 may be chosen, but should preferably be within arange of 0.5 to 10 seconds. As a result, although sensing of individualR-waves continues to occur in both channels ECG1 and ECG2 when in theconcerned state 304, and the buffer of 12 R-R intervals continues to beupdated, the opportunities for changing from the concerned state 304 toanother state and the estimates of heart rate only occur once thethree-second timer expires. Upon initial entry to the concerned state304, it is advantageous to process the most recent three-seconds of ECGdata, i.e., ECG data for the three seconds leading up to the transitionto the concerned state 304. This requires a continuous circularbuffering of the most recent three seconds of ECG data even while in thenot concerned state 302.

While in the concerned state 304, the present invention determines howsinusoidal and how noisy the signals are in order to determine thelikelihood that a ventricular fibrillation (VF) or fast ventriculartachycardia (VT) event is taking place, since the more sinusoidal andlow noise the signal is, the more likely a VT/VF event is taking place.As illustrated in FIG. 4, once the device transitions from the notconcerned state 302 to the concerned state 304, Block 305, a buffer foreach of the two channels ECG 1 and ECG2 for storing classifications of3-second segments of data as “shockable” or “non-shockable” is cleared.Processing of signals of the two channels ECG1 and ECG2 while in theconcerned state 304 is then triggered by the three second time period,rather than by the sensing of an R-wave utilized during the notconcerned state 302.

Once the three second time interval has expired, YES in Block 341,morphology characteristics of the signal during the three second timeinterval for each channel are utilized to determine whether the signalsare likely corrupted by noise artifacts and to characterize themorphology of the signal as “shockable” or “not shockable”. For example,using the signals associated with the three second time interval, adetermination is made for each channel ECG1 and ECG 2 as to whether thechannel is likely corrupted by noise, Block 342, and a determination isthen made as to whether both channels ECG1 and ECG2 are corrupted bynoise, Block 344.

FIG. 5 is a flowchart of a method of determining noise according to anembodiment of the present disclosure. As illustrated in FIG. 5, thedetermination as to whether the signal associated with each of thechannels ECG1 and ECG2 is likely corrupted by noise, Block 342 of FIG.4, includes multiple sequential noise tests that are performed on eachchannel ECG and ECG2. During a first noise test, for example, adetermination is made as to whether a metric of signal energy content ofthe signal for the channel is within predetermined limits, Block 380.For example, the amplitude of each sample associated with the threesecond window is determined, resulting in N sample amplitudes, fromwhich a mean rectified amplitude is calculated as the ratio of the sumof the rectified sample amplitudes to the total number of sampleamplitudes N for the segment. If the sampling rate is 256 samples persecond, for example, the total number of sample amplitudes N for thethree-second segment would be N=768 samples.

Once the mean rectified amplitude is calculated, a determination is madeas to whether the mean rectified amplitude is between an upper averageamplitude limit and a lower average amplitude limit, the lower averageamplitude limit being associated with asystole episodes without artifactand the upper average amplitude limit being associated with a valuegreater than what would be associated with ventricular tachycardia andventricular fibrillation events. According to an embodiment of thepresent invention, the upper average amplitude limit is set as 1.5 mV,and the lower average amplitude limit is set as 0.013 mV. While themetric of signal energy content is described above as the mean rectifiedamplitude, it is understood that other signal of energy contents couldbe utilized.

If the determined mean rectified amplitude is not between the upperaverage amplitude limit and the lower average amplitude limit, the threesecond segment for that channel is identified as being likely corruptedwith noise, Block 386, and no further noise tests are initiated for thatchannel's segment.

If the determined mean rectified amplitude is located between the upperaverage amplitude limit and the lower average amplitude limit, a noiseto signal ratio is calculated and a determination is made as to whetherthe noise to signal ratio is less than a predetermined noise to signalthreshold, Block 382. For example, the amplitude of each sampleassociated with the three second window is determined, resulting in Nraw sample amplitudes. The raw signal is lowpass filtered, resulting inL lowpass sample amplitudes. The raw mean rectified amplitude isdetermined as the average of the absolute values of the raw sampleamplitudes. The lowpass mean rectified amplitude is determined as theaverage of the absolute values of the lowpass sample amplitudes. Next, ahighpass mean rectified amplitude is then calculated as the differencebetween the raw mean rectified amplitude and the lowpass mean rectifiedamplitude. The noise to signal ratio is then determined as the ratio ofthe highpass mean rectified amplitude to the lowpass mean rectifiedamplitude. If the noise to signal ratio is greater than a predeterminedthreshold, such as 0.0703, for example, the three second segment forthat channel is identified as being likely corrupted with noise, Block386, and no further noise tests are initiated for the segment.

If the noise to signal ratio is less than or equal to the predeterminedthreshold, a determination is made as to whether the signal is corruptedby muscle noise, Block 384. According to an embodiment of the presentinvention, the determination as to whether the signal is corrupted bymuscle noise is made by determining whether the signal includes apredetermined number of signal inflections indicative of the likelihoodof the signal being corrupted by muscle noise, using a muscle noisepulse count that is calculated to quantify the number of signalinflections in the three second interval for each channel ECG1 and ECG2.The presence of a significant number of inflections is likely indicativeof muscle noise.

FIG. 6A is a graphical representation of a determination of whether asignal is corrupted by muscle noise according to an embodiment of thepresent invention. FIG. 6B is a flowchart of a method of determiningwhether a signal is corrupted by muscle noise according to an embodimentof the present invention. For example, as illustrated in FIGS. 6A and6B, in order to determine a muscle noise count for the three secondinterval, the raw signal 420 is applied to a first order derivativefilter to obtain a derivative signal 422, and all of the zero-crossings424 in the derivative signal 422 are located, Block 460. A data paircorresponding to the data points immediately prior to and subsequent tothe zero crossings 424, points 426 and 428 respectively, for eachcrossing is obtained. The value of the data point in each data pair withsmaller absolute value is zeroed in order to allow a clear demarcationof each pulse when a rectified signal 430 is derived from the derivativesignal 422 with zeroed zero-crossing points 432.

A pulse amplitude threshold Td, for determining whether the identifiedinflection is of a significant amplitude to be identified as beingassociated with muscle noise, is determined, Block 462, by dividing therectified signal from the three second segment into equal sub-segments434, estimating a local maximum amplitude 436-442 for each of thesub-segments 434, and determining whether the local amplitudes 436-442are less than a portion of the maximum amplitude, which is maximumamplitude 440 in the example of FIG. 6A, for the whole three secondsegment. If the local maximum amplitude is less than the portion of themaximum amplitude for the whole three second segment, the local maximumamplitude is replaced by the maximum for the whole three second segmentfor the sub-segment corresponding to that local maximum amplitude.

It is understood that while only two or less zero-crossing points areshown as being located within the sub-segments in the illustration ofFIG. 6A for the sake of simplicity, in fact each of the sub-segments434, which have a length of approximately 750 milliseconds, will containmany inflections, such as every 25 milliseconds, for example.

According to an embodiment of the present invention, the three secondsegment is divided into four sub-segments and the local maximumamplitudes are replaced by the maximum amplitude for the whole segmentif the local maximum amplitude is less than one fifth of the maximumamplitude for the whole segment. Once the determination of whether toreplace the local maximum amplitudes for each of the sub-segments withthe maximum amplitude for the whole segment is completed, the pulseamplitude threshold Td for the segment is set equal to a predeterminedfraction of the mean of the local maximum amplitudes for each of thesub-segments. According to an embodiment of the present invention, thepulse amplitude threshold Td for the three second segment is set equalto one sixth of the mean of the local maximum amplitudes 436-440.

Once the pulse amplitude threshold Td has been determined, theinflections associated with the signal for the three second segment isclassified as being of significant level to be likely indicative ofnoise by determining whether the pulse amplitude threshold Td is lessthan a pulse threshold, Block 464. According to an embodiment of thepresent invention, the pulse threshold is set as 1 microvolt. If thepulse amplitude threshold Td is less than the pulse threshold, thesignal strength is too small for a determination of muscle noise, andtherefore the signal is determined to be not likely corrupted by noiseand therefore the channel is determined to be not noise corrupted, Block466.

If the pulse amplitude threshold Td is greater than or equal to thepulse threshold, the three second segment is divided into twelvesub-segments of 250 ms window length, the number of muscle noise pulsesin each sub-segment is counted, and both the sub-segment having themaximum number of muscle noise pulses and the number of sub-segmentshaving 6 or more muscle noise pulses that are greater than apredetermined minimum threshold is determined. Muscle noise isdetermined to be present in the signal if either the maximum number ofmuscle noise pulses in a single sub-segment is greater than a noisepulse number threshold or the number of sub-segments of the twelvesub-segments having 6 or more muscle noise pulses greater than theminimum threshold is greater than or equal to a sub-segment pulse countthreshold. According to an embodiment of the present invention, thenoise pulse number threshold is set equal to eight and the sub-segmentpulse count threshold is set equal to three.

For example, if the pulse amplitude threshold Td is greater than orequal to the pulse threshold, No in Block 464, the maximum number ofmuscle noise counts in a single sub-segment is determined, Block 468. Ifthe maximum number of muscle noise counts is greater than the noisepulse number threshold, Yes in Block 470, the channel is determined tobe noise corrupted, Block 472. If the maximum number of muscle noisecounts for the channel is less than or equal to the noise pulse numberthreshold, No in Block 470, the number of sub-segments of the twelvesub-segments having 6 or more muscle noise pulses greater than theminimum threshold is determined, Block 474, and if the number is greaterthan or equal to a sub-segment pulse count threshold, Yes in Block 476,the channel is determined to be noise corrupted, Block 472. If thenumber is less than the sub-segment pulse count threshold, No in Block476, the channel is determined not to be noise corrupted, Block 466.

FIG. 6C is a flowchart of a method of determining whether a signal iscorrupted by muscle noise according to an embodiment of the presentinvention. Since muscle noise can be present during an episode ofventricular tachycardia, the width of the overall signal pulse waveformis determined in order to distinguish between signals that aredetermined likely to be purely noise related and signals that are bothshockable events and determined to include noise. Therefore, asillustrated in FIG. 6C, according to an embodiment of the presentinvention, once muscle noise is determined to be present as a result ofthe muscle noise pulse count being satisfied, No in Block 470 and Yes inBlock 476, a determination is made as to whether the signal is bothnoise corrupted and shockable, Block 480.

According to an embodiment of the present invention, the determinationin Block 480 as to whether the signal is both noisy and shockable ismade, for example, by dividing the rectified signal, having 768 datapoints, into four sub-segments and determining a maximum amplitude foreach of the four sub-segments by determining whether a maximum amplitudefor the sub-segment is less than a portion of the maximum amplitude forthe entire rectified signal in the three second segment. For example, adetermination is made for each sub-segment as to whether the maximumamplitude for the sub-segment is less than one fourth of the maximumamplitude for the entire rectified signal. If less than a portion of themaximum amplitude for the entire rectified signal in the three secondsegment, the maximum amplitude for the sub-segment is set equal to themaximum amplitude for the entire rectified signal.

A mean rectified amplitude for each of the sub-segments is determined bydividing the sum of the rectified amplitudes for the sub-segment by thenumber of samples in the sub-segment, i.e., 768÷4. Then the normalizedmean rectified amplitude for each sub-segment is determined by dividingthe mean rectified amplitude for each of the sub-segments by the peakamplitude for the sub-segment. The normalized mean rectified amplitudefor the three second segment is then determined as the sum of thenormalized mean rectified amplitudes for each sub-segment divided by thenumber of sub-segments, i.e., four.

Therefore, once muscle noise is suspected as a result of thedetermination of the muscle noise pulse count, the determination ofBlock 480 based on whether the normalized mean rectified amplitude forthe three second segment is greater than a predetermined threshold foridentifying signals that, despite being indicative of a likelihood ofbeing associated with noise, nevertheless are associated with ashockable event. For example, according to an embodiment of the presentinvention, a determination is made as to whether the normalized meanrectified amplitude for the three second segment is greater than 18microvolts. If the normalized mean rectified amplitude for the threesecond segment is less than or equal to the predetermined threshold, thechannel is likely corrupted by muscle noise and not shockable, No inBlock 480, and is therefore identified as being corrupted by noise,Block 472. If the normalized mean rectified amplitude for the threesecond segment is greater than the predetermined threshold, the channelis determined to be likely corrupted by muscle noise and shockable, Yesin Block 480, and is therefore identified as not to be likely corruptedby muscle noise, Block 478.

Returning to FIG. 5, when the signal is determined to be not likelycorrupted by muscle noise, a determination is made as to whether themean frequency of the signal associated with the channel is less than apredetermined mean frequency threshold, Block 388, such as 11 Hz forexample. The mean frequency of the signal during the 3 second segmentfor each channel ECG 1 and ECG2 is generated, for example, bycalculating the ratio of the mean absolute amplitude of the firstderivative of the 3 second segment to the mean absolute amplitude of the3 second segment, multiplied by a constant scaling factor. If the meanfrequency is determined to be greater than or equal to the predeterminedmean frequency threshold, No in Block 388, the three second segment forthat channel is identified as being likely corrupted with noise, Block386. If the mean frequency is determined to be less than thepredetermined mean frequency threshold, Yes in Block 388, the threesecond segment for that channel is identified as being not noisecorrupted, Block 390.

According to an embodiment of the present invention, since the meanspectral frequency tends to be low for true ventricular fibrillationevents, moderate for organized rhythms such as sinus rhythm andsupraventricular tachycardia, for example, and high during asystole andnoise, the determination in Block 388 includes determining whether themean frequency is less than a predetermined upper mean frequencythreshold, such as 11 Hz (i.e., mean period T of approximately 91milliseconds) for example, and whether the mean frequency is less than apredetermined lower mean frequency, such as 3 Hz for example. If themean frequency is below a second, lower threshold, such as 3 Hz, forexample, the signal is also rejected as noise and no further noise testsare initiated. This comparison of the mean frequency to a second lowerthreshold is intended to identify instances of oversensing, resulting inappropriate transition to the concerned state. If the mean frequency ofthe signal is less than 3 Hz, it is generally not possible for the heartrate to be greater than 180 beats per minute. In practice, it may beadvantageous to set the lower frequency threshold equal to theprogrammed VT/VF detection rate, which is typically approximately 3 Hz.

Therefore, in the determination of Block 388, if the mean frequency isdetermined to be either greater than or equal to the predetermined uppermean frequency threshold or less than the lower threshold, the threesecond segment for that channel is identified as being likely corruptedwith noise, Block 386. If the mean frequency is determined to be bothless than the predetermined upper mean frequency threshold and greaterthan the lower threshold, the three second segment for that channel isidentified as not being noise corrupted, Block 390.

Returning to FIG. 4, once the determination as to whether the channelsECG1 and ECG2 are corrupted by noise is made, Block 342, a determinationis made as to whether both channels are determined to be noisecorrupted, Block 344. If the signal associated with both channels ECG1and ECG2 is determined to likely be corrupted by noise, both channelsare classified as being not shockable, Block 347, and therefore a bufferfor each channel ECG1 and ECG 2 containing the last threeclassifications of the channel is updated accordingly and the process isrepeated for the next three-second windows. If both channels ECG1 andECG2 are not determined to be likely corrupted by noise, No in Block344, the device distinguishes between either one of the channels beingnot corrupted by noise or both channels being not corrupted by noise bydetermining whether noise was determined to be likely in only one of thetwo channels ECG1 and ECG2, Block 346.

If noise was likely in only one of the two channels, a determination ismade whether the signal for the channel not corrupted by noise, i.e.,the clean channel, is more likely associated with a VT event or with aVF event by determining, for example, whether the signal for thatchannel includes R-R intervals that are regular and the channel can betherefore classified as being relatively stable, Block 348. If the R-Rintervals are determined not to be relatively stable, NO in Block 348,the signal for that channel is identified as likely being associatedwith VF, which is then verified by determining whether the signal is ina VF shock zone, Block 350, described below. If R-R intervals for thatchannel are determined to be stable, YES in Block 348, the signal isidentified as likely being associated with VT, which is then verified bydetermining whether the signal is in a VT shock zone, Block 352,described below.

If noise was not likely for both of the channels, No in Block 346, i.e.,both channels are determined to be clean channels, a determination ismade whether the signal for both channels is more likely associated witha VT event or with a VF event by determining whether the signal for bothchannels includes R-R intervals that are regular and can be thereforeclassified as being relatively stable, Block 356. The determination inBlock 356 of whether the R-R intervals are determined to be relativelystable may be made using the method described in U.S. Pat. No. 7,894,894to Stadler et al., incorporated herein by reference in it's entirety. Ifthe R-R intervals are determined not to be relatively stable, NO inBlock 356, the signal for both channels is identified as likely beingassociated with VF, which is then verified by determining whether thesignal for each channel is in a VF shock zone, Block 360, describedbelow. If R-R intervals for both channels are determined to be stable,YES in Block 356, the signal is identified as likely being associatedwith VT, which is then verified by determining, based on both channels,whether the signal is in a VT shock zone, Block 358.

FIG. 7 is a graphical representation of a VF shock zone according to anembodiment of the present invention. As illustrated in FIG. 7, a VFshock zone 500 is defined for each channel ECG1 and ECG2 based on therelationship between the calculated low slope content and the spectralwidth associated with the channel. For example, the shock zone isdefined by a first boundary 502 associated with the low slope contentset for by the equation:

Low slope content=−0.0013×spectral width+0.415   Equation 1

and a second boundary 504 associated with the spectral width set forthby the equation:

spectral width=200   Equation 2

The low slope content metric is calculated as the ratio of the number ofdata points with low slope to the total number of samples in the3-second segment. For example, according to an embodiment of the presentinvention, the difference between successive ECG samples is determinedas an approximation of the first derivative (i.e, the slope) of the ECGsignal. In particular, the raw signal for each channel is applied to afirst order derivative filter to obtain a derivative signal for thethree-second segment. The derivative signal is then rectified, dividedinto four equal sub-segments, and the largest absolute slope isestimated for each of the four sub-segments.

A determination is made as to whether the largest absolute slopes areless than a portion of the overall largest absolute slope for the wholethree-second segment, such as one-fifth of the overall absolute slope,for example. If the largest absolute slope is less than the portion ofthe overall slope, then the slope value for that sub-segment is setequal to the overall largest absolute slope. If the largest absoluteslope is not less than the portion of the overall slope, then the slopevalue for that sub-segment is set equal to the determined largestabsolute slope for the sub-segment.

Once the slope value for each of the sub-segments has been determinedand updated by being set equal to the largest slope for the three secondsegment, if necessary, the average of the four slopes is calculated anddivided by a predetermined factor, such as 16 for example, to obtain alow slope threshold. The low slope content is then obtained bydetermining the number of sample points in the three-second segmenthaving an absolute slope less than or equal to the low slope threshold.

According to an embodiment of the present invention, if, during thedetermination of the low slope threshold, the low slope threshold is afraction, rather than a whole number, a correction is made to the lowslope content to add a corresponding fraction of the samples. Forexample, if the threshold is determined to be 4.5, then the low slopecontent is the number of sample points having an absolute slope lessthan or equal to 4 plus one half of the number of sample points withslope equal to 5.

The spectral width metric, which corresponds to an estimate of thespectral width of the signal for the three-second segment associatedwith each channel ECG1 and ECG2, is defined, for example, as thedifference between the mean frequency and the fundamental frequency ofthe signal. According to an embodiment of the present invention, thespectral width metric is calculated by determining the differencebetween the most recent estimate of the RR-cycle length and the meanspectral period of the signal for that channel. As is known in the art,the mean spectral period is the inverse of the mean spectral frequency.

As can be seen in FIG. 7, since noise 506 tends to have a relativelyhigher spectral width, and normal sinus rhythm 508 tends to have arelatively higher low slope content relative to VF, both noise 506 andnormal sinus rhythm 508 would be located outside the VF shock zone 500.

A determination is made for each channel ECG1 and ECG2 as to whether thelow slope content for that channel is less than both the first boundary502 and the spectral width is less than the second boundary 504, i.e.,the low slope content is less than −0.0013×spectral width+0.415, and thespectral width is less than 200. For example, once the event isdetermined to be associated with VF, i.e., the intervals for bothchannels are determined to be irregular, No in Block 356, adetermination is made that channel ECG1 is in the VF shock zone, Yes inBlock 360, if, for channel ECG1, both the low slope content is less thanthe first boundary 502 and the spectral width is less than the secondboundary 504. The three second segment for that channel ECG1 is thendetermined to be shockable, Block 363 and the associated buffer for thatchannel is updated accordingly. If either the low slope content for thechannel is not less than the first boundary 502 or the spectral width isnot less than the second boundary, the channel ECG1 is determined not tobe in the VF shock zone, No in Block 360, the three second segment forthat channel ECG1 is then determined to be not shockable, Block 365, andthe associated buffer is updated accordingly.

Similarly, a determination is made that channel ECG2 is in the VF shockzone, Yes in Block 362, if, for channel ECG2, both the low slope contentis less than the first boundary 502 and the spectral width is less thanthe second boundary 504. The three second segment for that channel ECG2is then determined to be shockable, Block 369 and the associated bufferfor that channel is updated accordingly. If either the low slope contentfor the channel is not less than the first boundary 502 or the spectralwidth is not less than the second boundary, the channel ECG2 isdetermined not to be in the VF shock zone, No in Block 362, the threesecond segment for that channel ECG2 is then determined to be notshockable, Block 367, and the associated buffer is updated accordingly.

FIGS. 8A and 8B are graphical representations of the determination ofwhether an event is within a shock zone according to an embodiment ofthe present invention. During the determination of whether the event iswithin the VT shock zone, Block 358 of FIG. 4, the low slope content andthe spectral width is determined for each channel ECG1 and ECG2, asdescribed above in reference to determining the VF shock zone. Adetermination is made as to which channel of the two signal channelsECG1 and ECG2 contains the minimum low slope content and which channelof the two signal channels ECG 1 and ECG2 contains the minimum spectralwidth. A first VT shock zone 520 is defined based on the relationshipbetween the low slope content associated with the channel determined tohave the minimum low slope content and the spectral width associatedwith the channel determined to have the minimum spectral width. Forexample, according to an embodiment of the present invention, the firstVT shock zone 520 is defined by a boundary 522 associated with theminimum low slope content and the minimum spectral width set forth bythe equation:

LSC=−0.004×SW+0.93   Equation 3

A second VT shock zone 524 is defined based on the relationship betweenthe low slope content associated with the channel determined to have theminimum low slope content and the normalized mean rectified amplitudeassociated with the channel determined to have the maximum normalizedmean rectified amplitude. In order to determine the normalized meanrectified amplitudes for the two channels ECG1 and ECG2 utilized duringthe VT shock zone test, the amplitude of each sample associated with thethree second window is determined, resulting in N sample amplitudes,from which a mean rectified amplitude is calculated as the ratio of thesum of the rectified sample amplitudes to the total number of sampleamplitudes N for the segment. If the sampling rate is 256 samples persecond, for example, the total number of sample amplitudes N for thethree-second segment would be N=768 samples.

According to an embodiment of the present invention, for example, thesecond VT shock zone 524 is defined by a second boundary 526 associatedwith the relationship between the minimum low slope count and themaximum normalized mean rectified amplitude set forth by the equation:

NMRA=68×LSC+8.16   Equation 4

If both the minimum low slope count is less than the first boundary 522,i.e., −0.004×minimum spectral width+0.93, and the maximum normalizedmean rectified amplitude is greater than the second boundary 526, i.e.,68×minimum low slope count+8.16, the event is determined to be in the VTshock zone, YES in Block 358, and both channels ECG1 and ECG2 aredetermined to be shockable, Block 357, and the associated buffers areupdated accordingly. If either the minimum low slope count is not lessthan the first boundary 522 or the maximum normalized mean rectifiedamplitude is not greater than the second boundary 526, the event isdetermined to be outside the VT shock zone, NO in Block 358, and bothchannels ECG1 and ECG2 are determined to be not shockable, Block 359.

As described, during both the VF shock zone test, Blocks 360 and 362,and the VT shock zone test, Block 358, the test results for each channelECG1 and ECG2 as being classified as shockable or not shockable arestored in a rolling buffer containing the most recent eight suchdesignations, for example, for each of the two channels ECG1 and ECG2that is utilized in the determination of Block 356, as described below.

If only one of the two channels ECG1 and ECG2 is determined to becorrupted by noise, Yes in Block 346, a determination is made whetherthe signal for the channel not corrupted by noise, i.e., the “cleanchannel”, is more likely associated with a VT event or with a VF eventby determining whether the signal for the clean channel includes R-Rintervals that are regular and can be therefore classified as beingrelatively stable, Block 348. If the R-R intervals are determined not tobe relatively stable, NO in Block 348, the signal for the clean channelis identified as likely being associated with VF, which is then verifiedby determining whether the signal for the clean channel is in a VF shockzone, Block 350, described below. If R-R intervals for the clean channelare determined to be stable, YES in Block 348, the signal is identifiedas likely being associated with VT, which is then verified bydetermining whether the signal for the clean channel is in a VT shockzone, Block 352.

According to an embodiment of the present invention, in order todetermine whether the signal for the clean channel includes R-Rintervals that are regular and the clean channel can be thereforeclassified as being either relatively stable, Yes in Block 348, orrelatively unstable, No in Block 348, the device discriminates VT eventsfrom VF events in Block 348 by determining whether the relative level ofvariation in the RR-intervals associated with the clean channel isregular. FIG. 9 is a flowchart of a method for discriminating cardiacevents according to an embodiment of the disclosure. For example, asillustrated in FIG. 9, predetermined maximum and minimum intervals forthe clean channel are identified from the updated buffer of 12RR-intervals, Block 342 of FIG. 4. According to an embodiment of thepresent invention, the largest RR-interval and the sixth largestRR-interval of the twelve RR-intervals are utilized as the maximuminterval and the minimum interval, respectively.

The difference between the maximum RR-interval and the minimumRR-interval of the 12 RR-intervals is calculated to generate an intervaldifference associated with the clean channel, 702. A determination isthen made as to whether the interval difference is greater than apredetermined stability threshold, Block 704, such as 110 milliseconds,for example.

If the interval difference is greater than the stability threshold, theevent is classified as an unstable event, Block 706, and therefore theclean channel is determined not to include regular intervals, No inBlock 348, and a determination is made as to whether the signalassociated with the clean channel is within a predetermined VF shockzone, Block 350 of FIG. 4, described below. If the interval differenceis less than or equal to the stability threshold, No in Block 704, thedevice determines whether the minimum RR interval is greater than aminimum interval threshold, Block 710, such as 200 milliseconds, forexample.

If the minimum interval is less than or equal to the minimum intervalthreshold, No in Block 710, the event is classified as an unstableevent, Block 706, and therefore the clean channel is determined not toinclude regular intervals, No in Block 348, and a determination is madeas to whether the signal associated with the clean channel is within apredetermined VF shock zone, Block 350 of FIG. 4, described below. Ifthe minimum interval is greater than the minimum interval threshold, Yesin Block 710, the device determines whether the maximum interval is lessthan or equal to a maximum interval threshold, Block 712, such as 333milliseconds for example. If the maximum interval is greater than themaximum interval threshold, the event is classified as an unstableevent, Block 706, and therefore the clean channel is determined not toinclude regular intervals, No in Block 348, and a determination is madeas to whether the signal associated with the clean channel is within apredetermined VF shock zone, Block 350 of FIG. 4, described below. Ifthe maximum interval is less than or equal to the maximum intervalthreshold, the event is classified as a stable event, Block 714, andtherefore the clean channel is determined to include regular intervals,Yes in Block 348, and a determination is made as to whether the signalassociated with the clean channel is within a predetermined VT shockzone, Block 352 of FIG. 4, described below.

Returning to FIG. 4, the determination of whether the clean channel iswithin the VF shock zone, Block 350, is made based upon a low slopecontent metric and a spectral width metric, similar to the VF shock zonedetermination described above in reference to Blocks 360 and 362, bothof which are determined for the clean channel using the method describedabove. Once the low slope content metric and a spectral width metric aredetermined for the clean channel, the determination of whether the cleanchannel is in the VF shock zone is made using Equations 1 and 2, so thatif either the low slope content for the clean channel is not less thanthe first boundary 502 or the spectral width is not less than the secondboundary 504, the clean channel is determined not to be in the VF zone,No in Block 350 and both channels are classified as not shockable, Block351, and the associated buffers are updated accordingly.

If the low slope content for the clean channel is less than the firstboundary 502 and the spectral width is less than the second boundary504, the clean channel is determined to be in the VF zone, Yes in Block350. A determination is then made as to whether the channel determinedto be corrupted by noise, i.e., the “noisy channel”, is within the VFshock zone, Block 354. If either the low slope content for the noisychannel is not less than the first boundary 502 or the spectral width isnot less than the second boundary 504, the noisy channel is determinednot to be in the VF zone, No in Block 354, the clean channel isclassified as shockable and the noisy channel is classified as notshockable, Block 355, and the associated buffers are updatedaccordingly.

If the low slope content for the noisy channel is less than the firstboundary 502 and the spectral width is less than the second boundary504, the noisy channel is determined to be in the VF zone, Yes in Block354, both the clean channel and the noisy channel are classified asbeing shockable, Block 353, and the associated buffers are updatedaccordingly.

Similar to the VT shock zone determination described above in referenceto Block 358, during the determination as to whether the clean channelis within the VT shock zone in Block 352, the low slope content and thespectral width is determined for the clean channel as described above inreference to determining the VF shock zone. The first VT shock zone 520is defined based on the relationship between the low slope content andthe spectral width associated with the clean channel according toEquation 3, for example, and the second VT shock zone 524 is definedbased on the relationship between the low slope count and the normalizedmean rectified amplitude associated with the clean channel. Thenormalized mean rectified amplitudes for the clean channel is the sameas described above in reference to the noise detection tests of Block344. For example, according to an embodiment of the present invention,the second VT shock zone 524 is defined by a second boundary 526associated with the relationship between the low slope count and thenormalized mean rectified amplitude of the clean channel using Equation4.

If both the low slope count is less than the first boundary 522, i.e.,−0.004×spectral width of clean channel+0.93, and the normalized meanrectified amplitude is greater than the second boundary 526, i.e.,68×low slope count of clean channel+8.16, the clean channel isdetermined to be in the VT shock zone, Yes in Block 352, both channelsare classified as being shockable, Block 353, and the associated buffersare updated accordingly.

If either the low slope count is not less than the first boundary 522 orthe maximum normalized mean rectified amplitude is not greater than thesecond boundary 526, the clean channel is determined to be outside theVT shock zone, No in Block 352, both channels are classified as beingnot shockable, Block 351, and the associated buffers are updatedaccordingly.

According to an embodiment of the present disclosure, in addition to theclassification of the sensing channels ECG1 and ECG2 as being shockableor not shockable using a gross morphology analysis, as described in FIG.4, for example, the device also determines whether periodic normal beatsare detected for one or both of the sensing channels, ECG1 and ECG2,Block 368. As a result, the decision on state transitions (e.g. as towhether to transition from the concerned operating state 304 to thearmed operating state 306 in Block 370, or from the armed state 306 tothe shock state 308) is made based on the results of both an analysis ofthe gross morphology of the signal in the three-second window or windowsfor each sensing channel ECG1 and ECG2, and a determination of whetherperiodic normal beats occur within one or more of the three-secondwindows for one or both sensing channel ECG1 and ECG2, as describedbelow. For a three-second segment to be classified as shockable, boththe gross morphology and periodic normal beats analysis have to classifythe same three-second segment as being shockable.

For example, according to an embodiment of the present invention, inorder to determine whether to transition from the concerned operatingstate 304 to the armed operating state 306, the device determineswhether a predetermined number, such as two out of three for example, ofthree-second segments for both channels ECG1 and ECG2 have beenclassified as being shockable during the gross morphology analysis,Blocks 353, 357, 363 and 369, and determines whether periodic normalbeats have been determined to occur for one or more of the three-secondsegments for the channels, Block 368. If the predetermined number ofthree-second segments in both channels ECG1 and ECG2 have beenclassified as shockable during both the gross morphology analysis andthe periodic normal beats detection, the device transitions from theconcerned state 304 to the armed state 306, Yes in Block 370. When thedevice determines to transition from the concerned state 304 to thearmed state 306, Yes in Block 370, processing continues to be triggeredby a three-second time out as is utilized during the concerned state304, described above.

If the predetermined number of three-second segments in both channelsECG1 and ECG2 have not been classified as shockable during both thegross morphology analysis and the periodic normal beats detection, thedevice does not transition from the concerned state 304 to the armedstate 306, No in Block 370, and a determination as to whether totransition back to the not concerned state 302 is made, Block 372. Thedetermination as to whether to transition from the concerned state 304back to the not concerned state 302 is made, for example, by determiningwhether a heart rate estimate is less than a heart rate threshold levelin both of the two channels ECG1 and ECG2, using the method fordetermining a heart rate estimate as described in U.S. Pat. No.7,894,894 to Stadler et al., incorporated herein by reference in it'sentirety. If it is determined that the device should not transition tothe not concerned state 302, i.e., either of the two heart rateestimates are greater than the heart rate threshold, No in Block 372,the process continues using the signal generated during a nextthree-second window, Block 341.

FIG. 10 is a flowchart of a method for performing periodic normal beatsanalysis during detection of arrhythmias in a medical device, accordingto an embodiment of the present disclosure. Therefore, as describedabove, in addition to performing the morphology analysis of the wholewaveform within the three-second windows associated with each sensingchannel ECG1 and ECG2, the device determines whether periodic normalbeats are detected within the sensing channels ECG1 and ECG2, Block 368of FIG. 4. In particular, as illustrated in FIG. 10, for eachthree-second sensing window associated with the respective sensingchannels ECG1 and ECG2, the device locates a single beat, i.e., R-wave,of the multiple beats in the three-second window, Block 720, andperforms a beat-based analysis of the single beat, Block 722. Accordingto an embodiment, for example, during the beat-based analysis, Block722, the device computes a normalized waveform area difference (NWAD)between the beat, also identified herein as “the unknown beat”, and apredetermined beat template, such as a normal sinus rhythm template, forexample, and determines whether the beat matches the template, Block724, based on the determined normalized waveform area difference, asdescribed below.

Using the results of the comparison of the beat to the template, thedevice determines whether the beat is either a match beat or a non-matchbeat, Block 724, by determining whether the beat matches the sinusrhythm template within a predetermined percentage, such as 60 percent,for example. If the beat matches the template by the predeterminedpercentage or greater, Yes in Block 724, the beat is identified as amatch beat, Block 726. If the beat matches the template by less than thepredetermined percentage, No in Block 724, the beat is identified as anon-match beat, Block 728.

FIG. 11 is a flowchart of a method for aligning an ECG signal of anunknown beat with a known morphology template for beat-based analysisduring detection of arrhythmias in a medical device, according to anembodiment of the present disclosure. In order to perform the comparisonof the unknown beat with the template in Block 724 of FIG. 10 toidentify the beat as being either a match beat or a non-match beat, theunknown beat must be aligned with the template. As illustrated in FIG.11, during alignment of the unknown beat with the template, Block 800,the device identifies individual beats within the three-second windowbased on determined R-wave sense signals, Block 802, and for each beatstores n points before and n points after the sample point on which theR-wave sense occurs. The 2n +1 sample points define an alignment windowwithin which an alignment point will be identified for alignment withthe clinician input or device generated template, such as a normal sinusrhythm template, for example. In one embodiment, the alignment window is53 sample points centered on the R-wave sense point. These sample pointsare stored in a memory buffer at block 804.

Once the sample points are determined for the beat, the devicedetermines a fourth order difference signal for the beat from thebuffered signal sample data, Block 806. The maximum slope of the fourthorder difference signal is determined and compared to a maximum slopethreshold, e.g. approximately 136 analog-to-digital (A/D) conversionunits, Block 808. If the slope threshold is not met, No in Block 808,the signal may be rejected as a weak signal, no further analysis of thatbeat is performed, and the process continues with the next beat in thethree-second window, Block 802. If the maximum slope is greater than thethreshold, Yes in Block 808, indicating that at least one pulsecorresponding to an R-wave is likely to be present in the alignmentwindow, pulses associate with the individual beat within the alignmentwindow are identified, Block 810.

To identify pulses associated with the beat within the alignment window,pulse criteria may be established, such as having a pulse width equal toat least some minimum number of sample points and a pulse amplitude ofat least some minimum amplitude. The number of pulses identified, orlack thereof, within the alignment window may be used to reject a“cardiac cycle” as a noisy cycle or a weak signal. One or more pulses,including negative-going and positive-going pulses, may be identifiedaccording to amplitude and pulse width criteria. In some examples, apulse may be identified based on a slope, maximum peak amplitude(positive or negative), pulse width or any combination thereof. If athreshold number of pulses is identified within the alignment window,the cycle may be considered a noisy cycle. While not shown explicitly inFIG. 11, a noisy cycle may be flagged or rejected for use in morphologyanalysis.

After identifying all pulses from the fourth order difference signal inthe alignment window, a pulse having a maximum pulse amplitude andhaving the same polarity as a stored template alignment point isidentified, Block 812. The sample point having the maximum pulseamplitude (absolute value) that also matches the polarity of thetemplate alignment point is identified and defined as the unknown signalalignment point.

An alignment shift is computed, Block 814, as the difference in samplepoint number between the alignment point identified, Block 812, and thepreviously established template alignment point. The alignment shift isthe number of sample points, that the unknown beat must be shifted inorder to align the unknown signal alignment point with the templatealignment point. The alignment shift is applied by shifting the unknownbeat sample points to align the unknown beat and the template over thealignment window, Block 816. The alignment shift may be applied to thefourth order difference signal itself if the template is stored as anensemble average of aligned fourth order difference signals or stored asthe fourth order difference signal of an ensemble average of aligned rawECG signals. The alignment shift may additionally or alternatively beapplied to the digitized raw signal sample points of the unknown signalwhen the template is the ensemble average of the raw signal samplepoints acquired during a known rhythm and aligned using the fourth orderdifference signal, as described in the template generation described incommonly assigned U.S. patent application Ser. No. 13/826,097,incorporated herein by reference in it's entirety. In another variation,the template may be the fourth order difference signal of ensembleaveraged raw signals, and the fourth order difference signal of theunknown raw signal is aligned with the fourth order difference template.

FIG. 12 is a flowchart of a method for computing a morphology metric todetermine the similarity between a known template aligned with anunknown cardiac cycle signal according to one embodiment. After aligningthe unknown beat and the template using the fourth order differencesignal alignment points, the morphology between the unknown beat and thetemplate is compared, Block 820. Numerous types of morphology analysiscould be used, such as wavelet analysis, comparisons of fiducial points(peak amplitude, zero crossings, maximum slopes, etc.) or othertechniques. In one embodiment, a NWAD is computed using a morphologyanalysis window that is a subset of, i.e. a number of sample points lessthan, the alignment window.

The operations performed by the device as described in conjunction withFIG. 12 may be performed on the aligned raw signal and correspondingtemplate and/or the aligned fourth order difference signal andcorresponding fourth order difference signal template.

As illustrated in FIG. 12, during the comparing of an individual beatwith the beat template, the device determines the R-wave width of theunknown signal, Block 822. In an illustrative embodiment, in order todetermine the R-wave width, the device determines an onset and an offsetpoint of the R-wave. During the determination of the onset and offset,the maximum positive pulse and the maximum negative of the fourth orderdifference signal are identified. The maximum positive pulse is anidentified pulse having positive polarity and maximum positive peakvalue; the maximum negative pulse is an identified pulse having negativepolarity and maximum absolute peak value. If the R wave has a positivepolarity in the raw ECG signal, the maximum positive pulse will precedethe maximum negative pulse on the 4th-order difference waveform. Anonset threshold is set based on the amplitude of the maximum positivepulse and an offset threshold is set based on the amplitude of themaximum negative pulse. For example, one-eighth of the peak amplitude ofthe maximum positive pulse may be defined as the onset threshold and oneeighth of the negative peak amplitude of the maximum negative pulse maybe defined as the offset threshold.

The onset of the R-wave is identified as the first sample point to theleft of the maximum positive pulse (e.g. moving from the pulse peakbackward in time to preceding sample points) to cross the onsetthreshold. The offset of the R-wave is identified as the first samplepoint to the right of the maximum negative pulse crossing the offsetthreshold. The R-wave width is the difference between the onset samplepoint number and the offset sample point number, i.e. the number ofsampling intervals between onset and offset.

For an R-wave having a negative polarity on the raw waveform, themaximum negative pulse will precede the maximum positive pulse on thefourth order difference signal. As such, the onset threshold is set as aproportion of the maximum negative peak amplitude of the maximumnegative pulse of the fourth order difference signal, and the offsetthreshold is set as a proportion of the maximum positive peak amplitudeof the maximum positive pulse. The R-wave onset is detected as the firstsample point to cross the onset threshold when moving left (earlier intime) from the maximum negative peak. The R-wave offset is detected asthe first sample point to cross the offset threshold moving right (laterin time) from the maximum positive peak. The R-wave width is thedifference between the onset sample point and the offset sample point.This method of computing an R-wave width based on onset and offsetpoints identified from the fourth order difference signal is illustratedbelow in FIG. 14.

The device sets a morphology analysis window in response to the R-wavewidth determined from the fourth order difference signal, Block 824. Themorphology of the R-wave itself is of greatest interest in classifyingthe unknown beat. Processing time can be reduced by comparing only thesample points of greatest interest without comparing extra points, forexample baseline points or Q- or S-wave points, preceding or followingthe R-wave. The morphology analysis window is therefore a proportion ofthe sample points that is less than the total number of sample pointsaligned in the alignment window.

In one embodiment, different ranges of R-wave width measurements may bedefined for which different respective sample numbers will be used toset the morphology analysis window. For example, if the R-wave width isgreater than 30 sample intervals, the morphology analysis window is setto a first number of sample points. If the R-wave width is greater than20 sample intervals but less than or equal to 30 sample intervals, themorphology analysis window is set to a second number of sample pointsless than the first number of sample points. If the R-wave width is lessthan or equal to 20 sample points, the morphology analysis window is setto a third number of sample points less than the second number of samplepoints. Two or more R-wave width ranges may be defined, each with acorresponding number of sample points defining the morphology analysiswindow. At least one of the R-wave width ranges is assigned a number ofsample points defining the morphology analysis window to be less thanthe alignment window. In some embodiments all of the R-wave width rangesare assigned a number of sample points defining the morphology analysiswindow to be less than the alignment window.

In the example given above, the alignment window is 53 sample points. Ifthe R-wave width is greater than 30 sample intervals, the morphologywindow is defined to be 48 sample points. The morphology analysis windowmay include 23 points preceding the R-wave sense point, the R-wave sensepoint itself, and 24 points after the R-wave sense point. If the R-wavewidth is greater than 20 but less than or equal to 30 sample intervals,the morphology window is defined to be 40 sample points (e.g. 19 beforethe R-wave sense point and 20 after the R-wave sense signal). If theR-wave width is less than or equal to 20 sample intervals, the window isdefined to be 30 sample points (e.g. 14 before and 15 points after theR-wave sense point and including the R-wave sense point).

In other embodiments, the number of sample points in the morphologyanalysis window may be defined as a fixed number of sample pointsgreater than the R-wave width, for example the R-wave width plus 12sample points. In another example, the number of sample points definingthe morphology analysis window may be computed as the R-wave width plusa rounded or truncated percentage of the R-wave width. For example, themorphology analysis window may be defined as the R-wave width plus fiftypercent of the R-wave width (i.e. 150% of the R-wave width), up to amaximum of the total alignment window or some portion less than thetotal alignment window.

The morphology window is applied to both the unknown beat and thetemplate. With the template and unknown cardiac signal aligned withinthe alignment window, the same number of sample points taken prior toand after the unknown beat alignment point is taken prior to and afterthe template alignment point.

After setting the morphology analysis window, Block 824, a morphologymetric of the similarity between the unknown signal and the template,such as the normalized waveform area difference (NWAD), for example, iscomputed, Block 826. Different methods maybe used to compute a NWAD. Inan illustrative method, the NWAD is computed by normalizing the absoluteamplitude of each of the unknown beat sample points and the templatesample points within the morphology window by a respective absolutemaximum peak amplitude value. A waveform area difference is thencalculated by summing the absolute amplitude differences between eachaligned pair of normalized sample points in the unknown signal and inthe template over the morphology window.

This waveform area difference may be normalized by a template area. Thetemplate area is computed as the sum of all of the absolute values ofthe normalized template sample points in the morphology window. The NWADis then calculated as the ratio of the waveform area difference to thetemplate area. The NWAD for the aligned signals is stored.

This NWAD may be compared to a threshold to classify the unknown beat asmatching the template based on a high correlation between the unknownbeat and the template evidenced by a NWAD exceeding a match threshold.One or more NWADs may be computed for a given unknown beat. In theexample shown in FIG. 12, additional NWADs may be computed by shiftingthe aligned template relative to the already aligned unknown signal byone or more sample points, Block 828. In one embodiment, the template isshifted by one sample point to the right, two sample points to theright, one sample point to the left and two sample points to the left toobtain five different alignments of the template and unknown signal. Foreach template alignment, i.e. with alignment points aligned, and withtemplate and unknown signal alignment points shifted relative to eachother by one point and two points in each direction, a NWAD is computed,Block 830. In this way, five NWADs are computed to measure thesimilarity between the unknown beat and the template (in aligned andshifted positions).

The device selects the NWAD having the greatest value as the morphologymetric for the unknown beat, which is then compared to the matchthreshold, Block 832, to classify the unknown beat as being either amatch beat or a non-match, Block 834, as described above in Blocks724-728 of FIG. 10.

FIG. 13 is an exemplary plot of alignment of an unknown beat and atemplate for computing a normalized waveform area difference duringbeat-based analysis, according to one embodiment. As illustrated in FIG.13, the unknown raw ECG signal 902 and the raw ECG signal template 904(ensemble average of n raw signals aligned using fourth order differencesignal) are used for determining a morphology match metric over amorphology analysis window 912. The width of the morphology analysiswindow 912 and the alignment of the unknown signal 902 and template 904are based on analysis of fourth order difference.

The raw ECG signal 902 is aligned with a template alignment point 906 ofthe template 904 of the raw ECG signal established during NSR,identified from an ensemble averaged fourth order difference signal asthe maximum absolute pulse amplitude value. An unknown signal alignmentpoint 908 is identified from the fourth order difference signal of theunknown raw ECG signal 902. The unknown signal alignment point 908 isthe maximum absolute pulse amplitude value having the same polarity asthe template alignment point 906.

After aligning the template 904 with the unknown raw ECG signal 902 overan alignment window 910, a morphology window 912 is set. The morphologywindow 912 is a subset of, i.e. shorter than or fewer sample pointsthan, the alignment window 910. The morphology window 912 is set basedon an R-wave width measured from the fourth order difference signal ofthe unknown signal as described below in conjunction with FIG. 14. Themorphology analysis window 912 is set in response to the R-wave widthmeasurement as some sample number greater than the R-wave width, asdescribed above.

The device determines a template area 914 as the sum of all of thenormalized absolute values of the template sample points within themorphology analysis window 912. The values are normalized by theabsolute value of the maximum amplitude of the template. The waveformarea difference 916 is computed as the summation of the absolute valuesof the differences between the aligned normalized absolute values of theunknown ECG signal sample points and the normalized absolute values ofthe template sample points. The NWAD is determined by taking the ratioof the waveform area difference 916 to the template area 914, which isthen used in the determination, Block 724, of whether the unknown beatis a match beat, Block 726, or a non-match beat, Block 728, in FIG. 10.

FIG. 14 is an exemplary plot illustrating a technique for determining anR-wave width and computing a normalized waveform area difference duringbeat-based analysis, according to another embodiment. In the exampleillustrated in FIG. 14, a fourth order difference signal 920 of theunknown raw ECG signal is aligned with a fourth order difference signaltemplate 922 for determining a morphology match metric over a morphologyanalysis window 930.

The unknown fourth order difference signal 920 is derived from theunknown raw ECG signal sensed by the device and is aligned with thefourth order difference template 922 established during NSR. Thetemplate alignment point 924 is identified as the maximum absolute pulseamplitude value of the fourth order difference template. The unknownsignal alignment point 926 is identified as the maximum absolute pulseamplitude value having the same polarity as the template alignment point924. The unknown fourth order difference signal 920 is shifted over thealignment window 928 by an alignment shift required to align the unknownsignal alignment point 926 with the template alignment point 924 asshown.

After aligning the template 922 with the unknown fourth order differencesignal 920 over alignment window 928, a morphology window 930 is set.The morphology window 930 is a subset of the alignment window 928 and isbased on an R-wave width 932 measured from the unknown fourth orderdifference signal 920.

In order to determine the R-wave width 932, the device determines thedifference between an R-wave onset point 934 and an R-wave offset point936 of the fourth order difference signal 920 of the unknown beat. Inorder to determine an R-wave onset point 934, the device determines amaximum positive pulse peak amplitude 938, and sets an onset threshold940 as a proportion of the maximum positive pulse peak amplitude 938. Inone embodiment, the device sets the onset threshold 940 as one-eighth ofthe maximum positive pulse peak amplitude 938. The onset point 934 isidentified as the first point to the left of the maximum positive pulsepeak crossing the onset threshold 940, i.e. equal to or greater than theonset threshold 940.

The device sets an offset threshold 942 as a proportion of a maximumnegative pulse peak amplitude 944, and the offset point 936 isidentified as the first point crossing the offset threshold 942 to theright of the maximum negative pulse. The device determines the R-wavewidth 932 as being the difference between the onset point 934 and theoffset point 936. The morphology analysis window 930 is set in responseto the R-wave width measurement as some sample number greater than theR-wave width 932, as described previously.

In other examples, the maximum negative pulse may occur earlier in thealignment window than the maximum positive pulse. If this is the case,the onset threshold is set as a proportion of the maximum negative pulsepeak amplitude and the onset point is determined as the first pointcrossing the onset threshold to the left of the maximum negative peak.Likewise, the offset threshold is set as a proportion of the maximumpositive pulse peak amplitude, and the offset point is determined as thefirst point to the right of the maximum positive pulse to cross theoffset threshold.

The morphology analysis window 930 may be centered on an R-wave sensesignal. In some embodiments, the morphology analysis window 930,determined from the fourth order difference signal 920, is applied tothe unknown raw ECG signal aligned with a raw ECG signal template, forexample analysis window 912 as shown in FIG. 13. The morphology matchmetric is determined from the raw ECG signal 902 and template 904. Inthe example illustrated in FIG. 14, the morphology analysis window 930is applied to the fourth order difference signal 920; the morphologymatch metric is determined from the fourth order difference signal 920and fourth order difference template 922.

The template area 946 is computed as the sum of all of the normalizedabsolute values of the template sample points within the morphologywindow 930. The values are normalized by the absolute value of themaximum amplitude of the template 922 (in this example point 926). Thedevice determines the waveform area difference 948 as the summation ofthe absolute differences between the aligned normalized absolute valuesof the unknown fourth order difference signal sample points and thenormalized absolute values of the template sample points. The NWAD isdetermined by the device as the ratio of the waveform area difference948 and the template area 946, and is compared to a match threshold toclassify the unknown beat corresponding to the fourth order differencesignal 920 as being either a match beat or a non-match beat, Blocks 726and 728 of FIG. 10.

Returning to FIG. 10, during the periodic normal beats analysis, Block368 of FIG. 4, once the individual beat is identified as being either amatch beat, Block 726, or a non-match beat, Block 728, using thenormalized waveform area difference analysis described above, forexample, the device determines whether an R-wave width associated withthe beat satisfies an R-wave width threshold, Block 730. For example,the R-wave width associated with the beat determined during the beatanalysis of Block 722, described above in reference to FIG. 14, iscompared to an R-wave template, and a determination of the differencebetween the R-wave associated with the beat and the template is made. Ifthe difference is less than or equal to a predetermined width differencethreshold, such as 22 milliseconds, for example, the beat is determinedto satisfy the R-wave width threshold, Yes in Block 730. On the otherhand, if the difference between the R-wave associated with the beat andthe template is greater than the predetermined width differencethreshold, the beat is determined to not satisfy the R-wave widththreshold, No in Block 730. If the beat is both a match beat, Block 726and satisfies the R-wave width threshold, Yes in Block 730, the beat isidentified as a normal beat, Block 732. If the beat is either anon-match beat, Block 728, or is a match beat, Block 726, but does notsatisfy the R-wave width threshold, No in Block 730, the beat isidentified as being a not normal beat, Block 734.

Once the beat is identified as either being either a normal beat, Block732, or a not normal beat, Block 734, the device determines whether thedetermination has been made for all of the beats in the three-secondwindow, Block 736. If the determination has not been made for all of thebeats in the three-second window, the process of identifying a beat asbeing either a match beat or a non-match beat and a normal beat or a notnormal beat, Blocks 720-734, is repeated for the next beat.

Once all of the beats within the three-second window have beenidentified as being either a normal beat, Block 732, or a not normalbeat, Block 734, Yes in Block 736, the device determines whetherperiodic normal beats are detected for the three-second window, Block738, as described below. If periodic normal beats are not detected, Noin Block 738, the three-second window is identified as being shockable,Block 740. If periodic normal beats are detected, Yes in Block 738, thethree-second window is identified as being not shockable, Block 742.

The resulting determination of the three-second window as beingidentified as one of shockable or not shockable based on the periodicnormal beats detection is then used, in combination with thedetermination of the sensing channel or channels being either shockableor not shockable, Blocks 353, 355, 357 and 363-369 of FIG. 4 during themorphology analysis of the whole waveform, described above, to determinestate transitions of the device. For example, if the three-secondsegment for the channel is identified as being shockable during thegross morphology analysis, and classified as not shockable during theperiodic normal beats analysis, i.e., periodic normal beats weredetected, then the three-second segment is classified as not beingshockable. On the other hand, if the three-second segment for thechannel is identified as being shockable during the gross morphologyanalysis, and classified as being shockable during the periodic normalbeats analysis, i.e., periodic normal beats were not detected, then thethree-second segment is classified as being shockable.

FIG. 15 is a flowchart of an exemplary method for determining whetherperiodic normal beats are detected within a predetermined sensing vectorduring the periodic normal beats analysis of FIG. 10. As illustrated inFIG. 15, according to one embodiment, in order to determine whetherperiodic normal beats are detected for the three-second window in Block738 of FIG. 10, the device may determine whether the number of normalbeats identified within the three-second window is greater than or equalto a predetermined threshold, Block 750. For example, according to oneembodiment, the device determines whether four or more normal beats wereidentified in the three-second window. If the number of normal beatsidentified in the three-second window is not greater than or equal tothe predetermined threshold, No Block 750, periodic normal beats are notdetected for the window, and the result of the periodic normal beatsdetection is to identify the three-second window as being shockable,Block 740.

In addition to determining whether the number of normal beats identifiedin the three-second window is greater than or equal to the predeterminedthreshold, Yes in Block 750, the device may determine whether an RRinterval associated with the four or more periodic beats is less than anRR interval threshold, Block 752, such as 300 milliseconds for example.If the RR interval associated with the four or more periodic beats isless than the RR interval threshold, Yes in Block 752, the devicedetermines whether the determination has been performed for all of theidentified normal beats, Block 751. If the determination has been madefor all of the RR intervals associated with the four or more beats, Yesin Block 751, and therefore the RR intervals have been determined to beless than the RR interval, the result of the periodic normal beatsdetection is to identify the three-second window as being shockable,Block 740. If the determination has not been made for all of the RRintervals, No in Block 751, the next one of the RR intervals is comparedto the RR interval threshold in Block 752, and the process is repeatedfor the next interval.

If the RR interval associated with the four or more periodic beats isgreater than or equal to the RR interval threshold, No in Block 752, thedevice may also determine whether the RR intervals are within a relativeinterval range relative to that interval, Block 754. If the RR intervalsare not within the relative interval range, No in Block 754, the devicedetermines whether the determination for Block 752 has been performedfor all of the intervals associated with the identified normal beats,Block 751. If the determination as to whether the RR interval is lessthan the RR interval threshold has been made for all of the RR intervalsassociated with the four or more beats, Yes in Block 751, the result ofthe periodic normal beats detection is to identify the three-secondwindow as being shockable, Block 740. If the determination has not beenmade for all of the RR intervals, No in Block 751, the next one of theRR intervals is compared to the RR interval threshold in Block 752, andthe process is repeated for the next interval. If the RR intervals arewithin the relative interval range, Yes in Block 754, the result of theperiodic normal beats detection is to identify the three-second windowas being not shockable, Block 742.

It is understood that the device may perform the periodic normal beatsdetection using any of the periodic normal beats parameters, Blocks750-754, alone or in combination, and in any order to identify thethree-second window as being not shockable, Block 742, or shockable,Block 740.

FIG. 16 is a schematic diagram of an exemplary cardiac signal sensedwithin a sensing detection window during detection of a cardiac event.As illustrated in FIG. 16, the device senses a cardiac signal 800 viasensing channel ECG1 or ECG2 during a sensing window 802. In the exampleillustrated, while the cardiac signal 800 includes multiple sensed beats804, the device determines, as a result of the periodic normal beatsanalysis, Block 368 of FIG. 4, described above, that four beats 806-812of the multiple sensed beats 804 are classified as being normal beats,with the four normal beats 806-812 resulting in three RR intervals814-818.

Assuming one of the three RR intervals 814-818 is determined to begreater than or equal to the interval threshold, No in Block 752 of FIG.15, in order to determine whether the RR intervals are within a relativeinterval range, Block 754, the device compares the interval to each ofthe other intervals and determines whether the RR intervals are within apredetermined interval range, such as one sixteenth. For example,assuming the device has determined that interval 814 is not less thanthe RR interval threshold, No in Block 752, interval 814 is compared tointerval 816 and to interval 818. If the intervals 814-818 aredetermined to be within the interval range, i.e., intervals 816 and 818are within one sixteenth of interval 814, the RR intervals 814-816 aredetermined to be within a relative interval range, Yes in Block 754 ofFIG. 15, and the result of the periodic normal beats detection is toidentify the three-second window as being not shockable, Block 742. Ifthe intervals 814-818 are not determined to be within the intervalrange, i.e., one or both of intervals 816 and 818 are not within onesixteenth of interval 814, the RR intervals 814-816 are determined notto be within the relative interval range, No in Block 754 of FIG. 15,and the result of the periodic normal beats detection is to identify thethree-second window as being shockable, Block 740.

If the device had determined, for example, that interval 814 was greaterthan the interval threshold, Yes in Block 752, and that not all of theintervals had been compared to the RR interval threshold, No in Block753, the device would then compare one of the other intervals to the RRinterval threshold, Block 752, and the process is repeated using thatinterval. For example, if interval 816 is determined to be not less thanthe RR interval threshold, No in Block 752, interval 816 is compared tointerval 814 and to interval 818, and if the intervals 814-818 aredetermined to be within the interval range, i.e., intervals 814 and 818are within one sixteenth of interval 816, the RR intervals 814-816 aredetermined to be within a relative interval range, Yes in Block 754 ofFIG. 15, and the result of the periodic normal beats detection is toidentify the three-second window as being not shockable, Block 742. Ifthe intervals 814-818 are not determined to be within the intervalrange, i.e., one or both of intervals 814 and 818 are not within onesixteenth of interval 816, the RR intervals 814-816 are determined notto be within the relative interval range, No in Block 754 of FIG. 15,and the result of the periodic normal beats detection is to identify thethree-second window as being shockable, Block 740.

In the same way, the process of one or both of Blocks 752 and 754 may beperformed using interval 816 and comparing intervals 814 and 816 tointerval 818 to determine whether the intervals are within the intervalrange for Block 754, as described above.

In this way, during the determination in Block 370 of FIG. 4 as towhether to advance from the concerned state 304 to the armed state 306,if the predetermined number of three-second segments in both channelsECG1 and ECG2 have not been classified as shockable during the grossmorphology analysis, i.e., both channels are not shockable (Blocks 351,355, 357, 359, 365 and 367), the device does not transition to the nextstate, No in Block 370, and a determination as to whether to transitionback to the not concerned state 302 is made, Block 372, as describedabove. If both channels are determined to be shockable during the grossmorphology analysis (Blocks 353, 357, 363 and 369), but one channel isdetermined to include periodic normal beats during the periodic normalbeat analysis described above, and therefore that channel is identifiedas being not shockable during the periodic normal beats analysis, thegross morphology determination of the channel being shockable isoverridden, resulting in both channels no longer being shockable. As aresult, the device does not transition to the next state, No in Block370, and a determination as to whether to transition back to the notconcerned state 302 is made, Block 372, as described above. On the otherhand, if both channels are determined to be shockable during the grossmorphology analysis (Blocks 353, 357, 363 and 369), and none of thechannels is determined to include periodic normal beats during theperiodic normal beat analysis described above, the device transitions tothe next state, Yes in Block 370, as described above.

FIG. 17 is a flowchart of an exemplary method for determining whetherperiodic normal beats are detected within a predetermined sensing vectorduring the periodic normal beats analysis of FIG. 10. According to oneexemplary embodiment, during the periodic normal beats analysis, Block368, the determination of whether periodic normal beats occur may bemade using two consecutive three-second sensing windows for the channelsECG1 and ECG2. In particular, the determination of whether beats arenormal beats Block 732 of FIG. 10 or not normal beats, Block 734, ismade for all of the beats in two consecutive sensing windows. Asillustrated in FIG. 17, according to an exemplary example, when twoconsecutive sensing are utilized, the device may determine whether thenumber of normal beats identified within the two three-second windows isgreater than or equal to a predetermined threshold, Block 760. Forexample, according to one embodiment, the device determines whether fouror more normal beats were identified in the two three-second windows. Ifthe number of normal beats identified in the two three-second window isnot greater than or equal to the predetermined threshold, No Block 760,periodic normal beats are not detected for the two three-second windows,and the result of the periodic normal beats detection is to identify thethree-second windows as being shockable, Block 740.

If the number of normal beats identified in the two three-second windowis greater than or equal to the predetermined threshold, Yes in Block760, the device may also determine whether the distribution of thenormal beats is greater than or equal to a normal beats distributionthreshold, Block 762. For example, according to one embodiment, thedevice determines whether one or more of the normal beats occurred inthe most recent three-second window of the two consecutive three-secondwindows. If the distribution of the normal beats is not greater than orequal to the normal beats distribution threshold, No in Block 762,periodic normal beats are not detected for the two three-second windows,and the result of the periodic normal beats detection is to identify thethree-second windows as being shockable, Block 740.

If the distribution of the normal beats is greater than or equal to thenormal beats distribution threshold, Yes in Block 762, the device maydetermine whether the total number of normal beats occurring in the twothree-second windows is less than or equal to a threshold total numberof normal beats, Block 764. The threshold number of total normal beatsmay be a predetermined number, for example, or may be a proportion ofthe total number of beats, both normal and not normal beats, detectedduring the two three-second windows, such as ⅜, for example. If thetotal number of normal beats occurring in the two three-second windowsis greater than, i.e., not less than or equal to, the threshold numberof total normal beats, No in Block 764, periodic normal beats are notdetected for the two three-second windows, and the result of theperiodic normal beats detection is to identify the three-second windowsas being shockable, Block 740.

If the total number of normal beats occurring in the two three-secondwindows is less than or equal to the threshold number of total normalbeats, Yes in Block 764, the device may determine whether an RR intervalassociated with the four or more periodic beats is less than an RRinterval threshold, Block 766, such as 300 milliseconds for example. Ifthe RR interval associated with the four or more periodic beats is lessthan the RR interval threshold, Yes in Block 766, the device determineswhether the determination has been performed for all of the identifiednormal beats, Block 765. If the determination has been made for all ofthe RR intervals associated with the four or more beats, Yes in Block765, and therefore all of the RR intervals have been determined to beless than the RR interval, the result of the periodic normal beatsdetection is to identify the three-second window as being shockable,Block 740. If the determination has not been made for all of the RRintervals, No in Block 765, the next one of the RR intervals is comparedto the RR interval threshold in Block 752, and the process is repeatedfor the next interval, as described above.

If an RR interval associated with the four or more periodic beats aregreater than or equal to the RR interval threshold, No in Block 766, thedevice may also determine whether the RR intervals are within a relativeinterval range of that interval, Block 768, such as one-sixteenth asdescribed above. If the RR intervals are not within the relativeinterval range, No in Block 768, the device determines whether thedetermination has been performed for all of the identified normal beats,Block 765. If the determination has been made for all of the RRintervals associated with the four or more beats, Yes in Block 765, andtherefore all of the RR intervals have been determined to be less thanthe RR interval, the result of the periodic normal beats detection is toidentify the three-second window as being shockable, Block 740. If thedetermination has not been made for all of the RR intervals associatedwith the four or more beats, No in Block 765, the process is repeatedusing a next beat, as described above. If the RR intervals are withinthe relative interval range, Yes in Block 768, the result of theperiodic normal beats detection is to identify the three-second windowas being not shockable, Block 742.

It is understood that the device may perform the periodic normal beatsdetection using any of the periodic normal beats parameters, Blocks760-768, alone or in combination, and in any order to identify thethree-second window as being not shockable, Block 742, or shockable,Block 740.

According to another embodiment, the device may also determine whetherthe RR intervals are within a relative interval range, Block 768, bydetermining whether, for any of the RR intervals, nRRi, two or more ofthe remaining RR intervals are determined to be one half of the RRinterval, nRRi, or twice the RR interval, nRRi. In addition, the devicemay determine the sum of the number of the normal RR intervals otherthan a current identified RR interval, nRRi, that fall within onesixteenth of the current RR interval, nRRi, and the number of the normalRR intervals other than the current identified RR interval, nRRi, thatare one half of the length of the current RR interval, nRRi, plus thenumber of the normal RR intervals other than the current identified RRinterval, nRRi, that are twice the length of the current RR interval,nRRi. If the total number of these RR intervals is greater than or equalto two, for example, then periodic normal beats are determined to occur,and the two three second windows are determined to be not shockable forthe periodic normal beats determination.

As a result, the decision on state transitions (e.g. as to whether totransition from the concerned operating state 304 to the armed operatingstate 306 in Block 370, or from the armed state 306 to the shock state308) is made based on the results of both an analysis of the grossmorphology of the signal in the three-second window or windows for eachsensing channel ECG1 and ECG2, and a determination of whether periodicnormal beats occur within one or more of the three-second windows forone or both sensing channel ECG1 and ECG2, as described below. For athree-second segment to be classified as shockable, both the grossmorphology and periodic normal beats analysis have to classify the samethree-second segment or segments as being shockable.

For example, according to an embodiment of the present invention, inorder to determine whether to transition from the concerned operatingstate 304 to the armed operating state 306, the device determineswhether a predetermined number, such as two out of three for example, ofthree-second segments for both channels ECG1 and ECG2 have beenclassified as being shockable during the gross morphology analysis,Blocks 353, 357, 363 and 369, and determines whether periodic normalbeats have been determined to occur for one or more of the three-secondsegments for the channels, Block 368. If the predetermined number ofthree-second segments in both channels ECG1 and ECG2 have beenclassified as shockable during both the gross morphology analysis andthe periodic normal beats detection, the device transitions from theconcerned state 304 to the armed state 306, Yes in Block 370. When thedevice determines to transition from the concerned state 304 to thearmed state 306, Yes in Block 370, processing continues to be triggeredby a three-second time out as is utilized during the concerned state304, described above.

If the predetermined number of three-second segments in both channelsECG1 and ECG2 have not been classified as shockable during both thegross morphology analysis and the periodic normal beats detection, thedevice does not transition from the concerned state 304 to the armedstate 306, No in Block 370, and a determination as to whether totransition back to the not concerned state 302 is made, Block 372. Thedetermination as to whether to transition from the concerned state 304back to the not concerned state 302 is made, for example, by determiningwhether a heart rate estimate is less than a heart rate threshold levelin both of the two channels ECG1 and ECG2, using the method fordetermining a heart rate estimate as described in U.S. Pat. No.7,894,894 to Stadler et al., incorporated herein by reference in it'sentirety. If it is determined that the device should not transition tothe not concerned state 302, i.e., either of the two heart rateestimates are greater than the heart rate threshold, No in Block 372,the process continues using the signal generated during a nextthree-second window, Block 341.

Thus, a method and apparatus for detecting a cardiac event have beenpresented in the foregoing description with reference to specificembodiments. It is appreciated that various modifications to thereferenced embodiments may be made without departing from the scope ofthe disclosure as set forth in the following claims.

We claim:
 1. A method of detecting a cardiac event in a medical device,comprising: sensing cardiac signals from a plurality of electrodes;sensing a plurality of beats in response to the sensed cardiac signals;identifying each beat of the plurality of beats as one of a normal beatand a not normal beat; determining at least one of whether a number ofbeats identified as a normal beat is greater than a normal beatthreshold, whether an RR interval associated with the beats identifiedas being a normal beat is less than a threshold interval, and whether RRintervals associated with the beats identified as being normal beats arewithin an RR interval range; and identifying the cardiac event as beingone of shockable and not shockable in response to the determining. 2.The method of claim 1, wherein the plurality of electrodes form a firstsensing vector and a second sensing vector, the method furthercomprising: performing a gross morphology analysis of a signal sensedalong the first sensing vector during a predetermined sensing window anda signal sensed along the second sensing vector during the predeterminedsensing window; and identifying the cardiac event as being one ofshockable and not shockable in response to the performed grossmorphology analysis.
 3. The method of claim 2, further comprisingdetermining whether to deliver a therapy to treat the cardiac event inresponse to both the identifying the cardiac event as being one ofshockable and not shockable in response to the determining and theidentifying the cardiac event as being one of shockable and notshockable in response to the performed gross morphology analysis.
 4. Themethod of claim 1, wherein determining whether RR intervals associatedwith the beats identified as being normal beats are within an RRinterval range comprises: comparing a duration of a first RR interval ofthe RR intervals associated with the beats identified as being normalbeats to durations of RR intervals of the RR intervals associated withthe beats identified as being normal beats other than the first RRinterval to generate interval differences; determining whether theinterval differences are less than a relative interval differencethreshold; and determining the RR intervals associated with the beatsidentified as being normal beats are within the RR interval range inresponse to all of the interval differences being less than the relativeinterval difference threshold.
 5. The method of claim 4, whereindetermining whether the interval differences are less than a relativeinterval difference threshold comprises determining whether thedurations of RR intervals of the RR intervals associated with the beatsidentified as being normal beats other than the first RR interval arewithin one sixteenth of the duration of the first RR interval.
 6. Themethod of claim 1, further comprising: determining a distribution of thebeats identified as being normal beats; comparing the determineddistribution of the beats identified as being normal beats to adistribution threshold; and further identifying the cardiac event asbeing one of shockable and not shockable in response to the comparing.7. The method of claim 1, further comprising: sensing the cardiacsignals over consecutive predetermined sensing windows, the consecutivepredetermined sensing windows comprising a first sensing window and asecond sensing window occurring subsequent to the first sensing window;determining a distribution of the beats identified as normal beatsoccurring within the first sensing vector and the second sensing vector;and further identifying the cardiac event as being one of shockable andnot shockable in response to the determined distribution.
 8. The methodof claim 7, wherein determining a distribution of the beats identifiedas normal beats occurring within the first sensing vector and the secondsensing vector comprises determining whether one or more of the beatsidentified as being normal beats occur within the second sensing window.9. The method of claim 1, further comprising: comparing a number ofbeats identified as being normal beats to a number identified as beingnot normal to a predetermined threshold; and further identifying thecardiac event as being one of shockable and not shockable in response tothe comparing.
 10. The method of claim 9, wherein the predeterminedthreshold comprises a proportion of the plurality of beats.
 11. Amedical device for detecting a cardiac event, comprising: a plurality ofelectrodes sensing cardiac signals having a plurality of beats; and aprocessor configured to identify each beat of the plurality of beats asone of a normal beat and a not normal beat, determine at least one ofwhether a number of beats identified as a normal beat is greater than anormal beat threshold, whether an RR interval associated with the beatsidentified as being a normal beat is less than a threshold interval, andwhether RR intervals associated with the beats identified as beingnormal beats are within an RR interval range, identifying the cardiacevent as being one of shockable and not shockable in response to thedetermining.
 12. The medical device of claim 11, wherein the pluralityof electrodes form a first sensing vector and a second sensing vector,the processor further configured to perform a gross morphology analysisof a signal sensed along the first sensing vector during a predeterminedsensing window and a signal sensed along the second sensing vectorduring the predetermined sensing window, and identify the cardiac eventas being one of shockable and not shockable in response to the performedgross morphology analysis.
 13. The medical device of claim 12, whereinthe processor is further configured to determine whether to deliver atherapy to treat the cardiac event in response to both the identifyingthe cardiac event as being one of shockable and not shockable inresponse to the determining and the identifying the cardiac event asbeing one of shockable and not shockable in response to the performedgross morphology analysis.
 14. The medical device of claim 11, whereindetermining whether RR intervals associated with the beats identified asbeing normal beats are within an RR interval range comprises: comparinga duration of a first RR interval of the RR intervals associated withthe beats identified as being normal beats to durations of RR intervalsof the RR intervals associated with the beats identified as being normalbeats other than the first RR interval to generate interval differences;determining whether the interval differences are less than a relativeinterval difference threshold; and determining the RR intervalsassociated with the beats identified as being normal beats are withinthe RR interval range in response to all of the interval differencesbeing less than the relative interval difference threshold.
 15. Themedical device of claim 14, wherein determining whether the intervaldifferences are less than a relative interval difference thresholdcomprises determining whether the durations of RR intervals of the RRintervals associated with the beats identified as being normal beatsother than the first RR interval are within one sixteenth of theduration of the first RR interval.
 16. The medical device of claim 11,wherein the processor is further configured to determine a distributionof the beats identified as being normal beats, compare the determineddistribution of the beats identified as being normal beats to adistribution threshold, and further identify the cardiac event as beingone of shockable and not shockable in response to the comparing.
 17. Themedical device of claim 11, wherein the processor is further configuredto sense the cardiac signals over consecutive predetermined sensingwindows, the consecutive predetermined sensing windows comprising afirst sensing window and a second sensing window occurring subsequent tothe first sensing window, determine a distribution of the beatsidentified as normal beats occurring within the first sensing vector andthe second sensing vector, and further identify the cardiac event asbeing one of shockable and not shockable in response to the determineddistribution.
 18. The medical device of claim 17, wherein determining adistribution of the beats identified as normal beats occurring withinthe first sensing vector and the second sensing vector comprisesdetermining whether one or more of the beats identified as being normalbeats occur within the second sensing window.
 19. The medical device ofclaim 11, wherein the processor is further configured to compare anumber of beats identified as being normal beats to a number identifiedas being not normal to a predetermined threshold, and further identifythe cardiac event as being one of shockable and not shockable inresponse to the comparing.
 20. The medical device of claim 19, whereinthe predetermined threshold comprises a proportion of the plurality ofbeats.